The structural connectivity of subthalamic deep brain stimulation correlates with impulsivity in Parkinson's disease

Improvement of the thalamocortical white matter network in people with stable treated relapsing-remitting multiple sclerosis over time

Advanced imaging techniques (tractography) enable the mapping of white matter (WM) pathways and the understanding of brain connectivity patterns. We combined tractography with a network-based approach to examine WM microstructure on a network level in people with relapsing-remitting multiple sclerosis (pw-RRMS) and healthy controls (HCs) over 2 years. Seventy-six pw-RRMS matched with 43 HCs underwent clinical assessments and 3T MRI scans at baseline (BL) and 2-year follow-up (2-YFU). Probabilistic tractography was performed, accounting for the effect of lesions, producing connectomes of 25 million streamlines. Network differences in fibre density across pw-RRMS and HCs at BL and 2-YFU were quantified using network-based statistics (NBS). Longitudinal network differences in fibre density were quantified using NBS in pw-RRMS, and were tested for correlations with disability, cognition and fatigue scores. Widespread network reductions in fibre density were found in pw-RRMS compared with HCs at BL in cortical regions, with more reductions detected at 2-YFU. Pw-RRMS had reduced fibre density at BL in the thalamocortical network compared to 2-YFU. This effect appeared after correction for age, was robust across different thresholds, and did not correlate with lesion volume or disease duration. Pw-RRMS demonstrated a robust and long-distance improvement in the thalamocortical WM network, regardless of age, disease burden, duration or therapy, suggesting a potential locus of neuroplasticity in MS. This network's role over the disease's lifespan and its potential implications in prognosis and treatment warrants further investigation.

Subthalamic Nucleus Stimulation Modulates Cognitive Theory of Mind in Parkinson's Disease

BACKGROUND

Theory of mind (ToM), the ability to infer others' mental state, is essential for social interaction among human beings. It has been widely reported that both cognitive (inference of knowledge) and affective (inference of emotion) components of ToM are disrupted in Parkinson's disease (PD). Previous studies usually focused on the involvement of the prefrontal cortex.

OBJECTIVE

This study investigated the causal role of the subthalamic nucleus (STN), a key hub of the fronto-basal ganglia loops, in ToM.

METHODS

Thirty-four patients with idiopathic PD (15 women, aged 62.2 ± 8.3 years) completed a Yoni task with deep brain stimulation (DBS) ON and OFF. The Yoni task was designed to separate the cognitive and affective components of ToM. Volumes of tissue activated (VTA) were computed for three subregions of the STN.

RESULTS

DBS showed insignificant effects on ToM inference costs at the group level, which may be due to the large interindividual variability. The associative VTA correlated with the cognitive inference cost change but not the affective inference cost change. Patients with greater associative STN stimulation infer more slowly on cognitive ToM. Stimulating associative STN can adversely affect cognitive ToM in PD patients, especially in patients with a wide range of stimulation (≥0.157) or cognitive decline (Montreal Cognitive Assessment < 26).

CONCLUSIONS

The associative STN plays a causal role in cognitive ToM in patients with PD. However, stimulating the associative STN likely impairs cognitive ToM and potentially leads to social interaction deficits in PD. © 2024 International Parkinson and Movement Disorder Society.

No evidence for an association of voxel-based morphometry with short-term non-motor outcomes in deep brain stimulation for Parkinson's disease

Deep brain stimulation of the subthalamic nucleus (STN-DBS) is an established therapy in advanced Parkinson's disease (PD). Motor and non-motor outcomes, however, show considerable inter-individual variability. Preoperative morphometry-based metrics have recently received increasing attention to explain treatment effects. As evidence for the prediction of non-motor outcomes is limited, we sought to investigate the association between metrics of voxel-based morphometry and short-term non-motor outcomes following STN-DBS in this prospective open-label study. Forty-nine PD patients underwent structural MRI and a comprehensive clinical assessment at preoperative baseline and 6-month follow-up. Voxel-based morphometry was used to assess associations between cerebral volume and non-motor outcomes corrected for multiple comparisons using a permutation-based approach. We replicated existing results associating volume loss of the superior frontal cortex with subpar motor outcomes. Overall non-motor burden, however, was not significantly associated with morphometric features, limiting its use as a marker to inform patient selection and holistic preoperative counselling.

A large normative connectome for exploring the tractographic correlates of focal brain interventions

Diffusion-weighted MRI (dMRI) is a widely used neuroimaging modality that permits the in vivo exploration of white matter connections in the human brain. Normative structural connectomics - the application of large-scale, group-derived dMRI datasets to out-of-sample cohorts - have increasingly been leveraged to study the network correlates of focal brain interventions, insults, and other regions-of-interest (ROIs). Here, we provide a normative, whole-brain connectome in MNI space that enables researchers to interrogate fiber streamlines that are likely perturbed by given ROIs, even in the absence of subject-specific dMRI data. Assembled from multi-shell dMRI data of 985 healthy Human Connectome Project subjects using generalized Q-sampling imaging and multispectral normalization techniques, this connectome comprises ~12 million unique streamlines, the largest to date. It has already been utilized in at least 18 peer-reviewed publications, most frequently in the context of neuromodulatory interventions like deep brain stimulation and focused ultrasound. Now publicly available, this connectome will constitute a useful tool for understanding the wider impact of focal brain perturbations on white matter architecture going forward.

Focused stimulation of dorsal versus ventral subthalamic nucleus enhances action-outcome learning in patients with Parkinson's disease

Deep brain stimulation of the subthalamic nucleus is an effective treatment for the clinical motor symptoms of Parkinson's disease, but may alter the ability to learn contingencies between stimuli, actions and outcomes. We investigated how stimulation of the functional subregions in the subthalamic nucleus (motor and cognitive regions) modulates stimulus-action-outcome learning in Parkinson's disease patients. Twelve Parkinson's disease patients with deep brain stimulation of the subthalamic nucleus completed a probabilistic stimulus-action-outcome task while undergoing ventral and dorsal subthalamic nucleus stimulation (within subjects, order counterbalanced). The task orthogonalized action choice and outcome valence, which created four action-outcome learning conditions: action-reward, inhibit-reward, action-punishment avoidance and inhibit-punishment avoidance. We compared the effects of deep brain stimulation on learning rates across these conditions as well as on computed Pavlovian learning biases. Dorsal stimulation was associated with higher overall learning proficiency relative to ventral subthalamic nucleus stimulation. Compared to ventral stimulation, stimulating the dorsal subthalamic nucleus led to a particular advantage in learning to inhibit action to produce desired outcomes (gain reward or avoid punishment) as well as better learning proficiency across all conditions providing reward opportunities. The Pavlovian reward bias was reduced with dorsal relative to ventral subthalamic nucleus stimulation, which was reflected by improved inhibit-reward learning. Our results show that focused stimulation in the dorsal compared to the ventral subthalamic nucleus is relatively more favourable for learning action-outcome contingencies and reduces the Pavlovian bias that could lead to reward-driven behaviour. Considering the effects of deep brain stimulation of the subthalamic nucleus on learning and behaviour could be important when optimizing stimulation parameters to avoid side effects like impulsive reward-driven behaviour.

Subjective feelings associated with expectations and rewards during risky decision-making in impulse control disorder

Impulse Control Disorder (ICD) in Parkinson's disease is a behavioral addiction induced by dopaminergic therapies, but otherwise unclear etiology. The current study investigates the interaction of reward processing variables, dopaminergic therapy, and risky decision-making and subjective feelings in patients with versus without ICD. Patients with (n = 18) and without (n = 12) ICD performed a risky decision-making task both 'on' and 'off' standard-of-care dopaminergic therapies (the task was performed on 2 different days with the order of on and off visits randomized for each patient). During each trial of the task, participants choose between two options, a gamble or a certain reward, and reported how they felt about decision outcomes. Subjective feelings of 'pleasure' are differentially driven by expectations of possible outcomes in patients with, versus without ICD. While off medication, the influence of expectations about risky-decisions on subjective feelings is reduced in patients with ICD versus without ICD. While on medication, the influence of expected outcomes in patients with ICD versus without ICD becomes similar. Computational modeling of behavior supports the idea that latent decision-making factors drive subjective feelings in patients with Parkinson's disease and that ICD status is associated with a change in the relationship between factors associated with risky behavior and subjective feelings about the experienced outcomes. Our results also suggest that dopaminergic medications modulate the impact expectations have on the participants' subjective reports. Altogether our results suggest that expectations about risky decisions may be decoupled from subjective feelings in patients with ICD, and that dopaminergic medications may reengage these circuits and increase emotional reactivity in patients with ICD.

Double dissociation of dopamine and subthalamic nucleus stimulation on effortful cost/benefit decision making

Deep brain stimulation (DBS) and dopaminergic therapy (DA) are common interventions for Parkinson's disease (PD). Both treatments typically improve patient outcomes, and both can have adverse side effects on decision making (e.g., impulsivity).1,2 Nevertheless, they are thought to act via different mechanisms within basal ganglia circuits.3 Here, we developed and formally evaluated their dissociable predictions within a single cost/benefit effort-based decision-making task. In the same patients, we manipulated DA medication status and subthalamic nucleus (STN) DBS status within and across sessions. Using a series of descriptive and computational modeling analyses of participant choices and their dynamics, we confirm a double dissociation: DA medication asymmetrically altered participants' sensitivities to benefits vs. effort costs of alternative choices (boosting the sensitivity to benefits while simultaneously lowering sensitivity to costs); whereas STN DBS lowered the decision threshold of such choices. To our knowledge, this is the first study to show, using a common modeling framework, a dissociation of DA and DBS within the same participants. As such, this work offers a comprehensive account for how different mechanisms impact decision making, and how impulsive behavior (present in DA-treated patients with PD and DBS patients) may emerge from separate physiological mechanisms.

Diffusion tensor imaging changes of the cortico-thalamic-striatal tracts correlate with fatigue and disability in people with relapsing-remitting MS

PURPOSE

To investigate how the microstructural neural integrity of cortico-thalamic-striatal (CTS) tracts correlate with fatigue and disability over time. The primary outcome was diffusion tensor imaging (DTI) metrics change over time, and the secondary outcome was correlations with fatigue and disability in people with RRMS (pw-RRMS).

METHODS

76 clinically stable pw-RRMS and 43 matched healthy controls (HCs). The pw-RRMS cohort consisted of three different treatment subgroups. All participants underwent disability, cognitive, fatigue and mental health assessments. Structural and diffusion scans were performed at baseline (BL) and 2-year follow-up (2-YFU) for all participants. Fractional anisotropy (FA), mean, radial and axial diffusivities (MD, RD, AD) of normal-appearing white matter (NAWM) and white matter lesion (WML) in nine tracts-of-interests (TOIs) were estimated using our MRtrix3 in-house pipeline.

RESULTS

We found significant BL and 2-YFU differences in most diffusion metrics in TOIs in pw-RRMS compared to HCs (pFDR ≤ 0.001; false-detection-rate (FDR)-corrected). There was a significant decrease in WML diffusivities and an increase in FA over the follow-up period in most TOIs (pFDR ≤ 0.001). Additionally, there were no differences in DTI parameters across treatment groups. AD and MD were positively correlated with fatigue scores (r ≤ 0.33, p ≤ 0.01) in NAWM-TOIs, while disability (EDSS) was negatively correlated with FA in most NAWM-TOIs (|r|≤0.31, p ≤ 0.01) at both time points. Disability scores correlated with all diffusivity parameters (r ≤ 0.29, p ≤ 0.01) in most WML-TOIs at both time points.

CONCLUSION

Statistically significant changes in diffusion metrics in WML might be indicative of integrity improvement over two years in CTS tracts in clinically stable pw-RRMS. This finding represents structural changes within lesioned tracts. Measuring diffusivity in pw-RRMS affected tracts might be a relevant measure for future remyelination clinical trials.

Modulation of limbic resting-state networks by subthalamic nucleus deep brain stimulation

Beyond the established effects of subthalamic nucleus deep brain stimulation (STN-DBS) in reducing motor symptoms in Parkinson's disease, recent evidence has highlighted the effect on non-motor symptoms. However, the impact of STN-DBS on disseminated networks remains unclear. This study aimed to perform a quantitative evaluation of network-specific modulation induced by STN-DBS using Leading Eigenvector Dynamics Analysis (LEiDA). We calculated the occupancy of resting-state networks (RSNs) in functional MRI data from 10 patients with Parkinson's disease implanted with STN-DBS and statistically compared between ON and OFF conditions. STN-DBS was found to specifically modulate the occupancy of networks overlapping with limbic RSNs. STN-DBS significantly increased the occupancy of an orbitofrontal limbic subsystem with respect to both DBS OFF (p = 0.0057) and 49 age-matched healthy controls (p = 0.0033). Occupancy of a diffuse limbic RSN was increased with STN-DBS OFF when compared with healthy controls (p = 0.021), but not when STN-DBS was ON, which indicates rebalancing of this network. These results highlight the modulatory effect of STN-DBS on components of the limbic system, particularly within the orbitofrontal cortex, a structure associated with reward processing. These results reinforce the value of quantitative biomarkers of RSN activity in evaluating the disseminated impact of brain stimulation techniques and the personalization of therapeutic strategies.

The altered spontaneous neural activity in patients with Parkinson's disease and its predictive value for the motor improvement of deep brain stimulation

BACKGROUND

This study aims to investigate the altered spontaneous neural activity in patients with Parkinson's disease (PD) revealed by amplitudes of low-frequency fluctuations (ALFF) of resting-state fMRI, and the feasibility of using ALFF as neuroimaging predictors for motor improvement after bilateral subthalamic nucleus (STN) deep brain stimulation (DBS).

METHODS

Fourty-four patients and 44 healthy controls were included in this study. First, the ALFF of patients with PD was compared with that of controls; then significant clusters were correlated with motor improvement after DBS (unified Parkinson's disease rating scale (UPDRS-III)) and other clinical variables. Second, regression and classification of the machine learning models were conducted to predict motor improvement after DBS. Receiver operating characteristic (ROC) analysis was used to evaluate the performance of the classification model.

RESULTS

Compared with healthy controls, patients with PD showed increased ALFF in the bilateral motor area and decreased ALFF in the bilateral temporal cortex and cerebellum. The Hoehn-Yahr stages correlated with ALFF within the bilateral cerebellum (p = 0.021), and UPDRS-III improvement correlated with ALFF in the left (p < 0.001) and right (p = 0.005) motor areas. The regression model showed a significant correlation between the predicted and observed UPDRS-III changes (R = 0.65, p < 0.001). The ROC analysis revealed an area under the curve (AUC) of 0.94 which differentiated moderate and superior DBS responders.

CONCLUSION

The results revealed altered ALFF patterns in patients with PD and their correlations with clinical variables. Both binary and continuous ALFF can potentially serve as predictive biomarkers for DBS response.

Lead-DBS v3.0: Mapping deep brain stimulation effects to local anatomy and global networks

Following its introduction in 2014 and with support of a broad international community, the open-source toolbox Lead-DBS has evolved into a comprehensive neuroimaging platform dedicated to localizing, reconstructing, and visualizing electrodes implanted in the human brain, in the context of deep brain stimulation (DBS) and epilepsy monitoring. Expanding clinical indications for DBS, increasing availability of related research tools, and a growing community of clinician-scientist researchers, however, have led to an ongoing need to maintain, update, and standardize the codebase of Lead-DBS. Major development efforts of the platform in recent years have now yielded an end-to-end solution for DBS-based neuroimaging analysis allowing comprehensive image preprocessing, lead localization, stimulation volume modeling, and statistical analysis within a single tool. The aim of the present manuscript is to introduce fundamental additions to the Lead-DBS pipeline including a deformation warpfield editor and novel algorithms for electrode localization. Furthermore, we introduce a total of three comprehensive tools to map DBS effects to local, tract- and brain network-levels. These updates are demonstrated using a single patient example (for subject-level analysis), as well as a retrospective cohort of 51 Parkinson's disease patients who underwent DBS of the subthalamic nucleus (for group-level analysis). Their applicability is further demonstrated by comparing the various methodological choices and the amount of explained variance in clinical outcomes across analysis streams. Finally, based on an increasing need to standardize folder and file naming specifications across research groups in neuroscience, we introduce the brain imaging data structure (BIDS) derivative standard for Lead-DBS. Thus, this multi-institutional collaborative effort represents an important stage in the evolution of a comprehensive, open-source pipeline for DBS imaging and connectomics.

Energy Delivered by Subthalamic Deep Brain Stimulation for Parkinson Disease Correlates With Depressive Personality Trait Shift

OBJECTIVES

Despite the large amount of literature examining the potential influence of subthalamic nucleus deep brain stimulation (STN-DBS) on psychiatric symptoms and cognitive disorders, only a few studies have focused on its effect on personality. We investigated the correlation between total electrical energy delivered (TEED) and the occurrence of depressive traits in patients with Parkinson disease (PD) after one year of DBS.

MATERIALS AND METHODS

Our study involved 20 patients with PD (12 women, mean [±SD] age 57.60 ± 7.63 years) who underwent bilateral STN-DBS, whose personality characteristics were assessed using the Minnesota Multiphasic Personality Inventory-2 (MMPI-2), according to the core assessment program for surgical interventional therapies in Parkinson's disease (CAPSIT-PD) procedure.

RESULTS

We found that despite a marked improvement in motor functions and quality of life after 12 months, patients showed a significant increase in MMPI-2 subscales for depression (D scale and Depression scale) and in other content component scales (low self-esteem, work interference, and negative treatment indicators). Interestingly, only the TEED on the right side was inversely correlated with the changes in scale D (r_s = -0.681, p = 0.007), whereas depressive traits did not correlate with disease duration, levodopa equivalent daily dose (LEDD) reduction, patient's age, or severity of motor symptoms.

CONCLUSIONS

Our preliminary observations indicate that despite the excellent motor outcome and general improvement in quality of life, DBS treatment can result in patients poorly adjusting to their personal, familiar, and socio-professional life. Different influences and multiple factors (such as TEED, intra/postsurgical procedure, coping mechanisms, and outcome expectations) may affect depressive traits. Further advances are expected to improve stimulation methods.

Magnetic Resonance Imaging Studies of Neurodegenerative Disease: From Methods to Translational Research

Neurodegenerative diseases (NDs) have become a significant threat to an aging human society. Numerous studies have been conducted in the past decades to clarify their pathologic mechanisms and search for reliable biomarkers. Magnetic resonance imaging (MRI) is a powerful tool for investigating structural and functional brain alterations in NDs. With the advantages of being non-invasive and non-radioactive, it has been frequently used in both animal research and large-scale clinical investigations. MRI may serve as a bridge connecting micro- and macro-level analysis and promoting bench-to-bed translational research. Nevertheless, due to the abundance and complexity of MRI techniques, exploiting their potential is not always straightforward. This review aims to briefly introduce research progress in clinical imaging studies and discuss possible strategies for applying MRI in translational ND research.

Deep brain-machine interfaces: sensing and modulating the human deep brain

Different from conventional brain-machine interfaces that focus more on decoding the cerebral cortex, deep brain-machine interfaces enable interactions between external machines and deep brain structures. They sense and modulate deep brain neural activities, aiming at function restoration, device control and therapeutic improvements. In this article, we provide an overview of multiple deep brain recording and stimulation techniques that can serve as deep brain-machine interfaces. We highlight two widely used interface technologies, namely deep brain stimulation and stereotactic electroencephalography, for technical trends, clinical applications and brain connectivity research. We discuss the potential to develop closed-loop deep brain-machine interfaces and achieve more effective and applicable systems for the treatment of neurological and psychiatric disorders.

Clinical neuroscience and neurotechnology: An amazing symbiosis

In the last decades, clinical neuroscience found a novel ally in neurotechnologies, devices able to record and stimulate electrical activity in the nervous system. These technologies improved the ability to diagnose and treat neural disorders. Neurotechnologies are concurrently enabling a deeper understanding of healthy and pathological dynamics of the nervous system through stimulation and recordings during brain implants. On the other hand, clinical neurosciences are not only driving neuroengineering toward the most relevant clinical issues, but are also shaping the neurotechnologies thanks to clinical advancements. For instance, understanding the etiology of a disease informs the location of a therapeutic stimulation, but also the way stimulation patterns should be designed to be more effective/naturalistic. Here, we describe cases of fruitful integration such as Deep Brain Stimulation and cortical interfaces to highlight how this symbiosis between clinical neuroscience and neurotechnology is closer to a novel integrated framework than to a simple interdisciplinary interaction.

Imaging the Limbic System in Parkinson's Disease-A Review of Limbic Pathology and Clinical Symptoms

The limbic system describes a complex of brain structures central for memory, learning, as well as goal directed and emotional behavior. In addition to pathological studies, recent findings using in vivo structural and functional imaging of the brain pinpoint the vulnerability of limbic structures to neurodegeneration in Parkinson's disease (PD) throughout the disease course. Accordingly, dysfunction of the limbic system is critically related to the symptom complex which characterizes PD, including neuropsychiatric, vegetative, and motor symptoms, and their heterogeneity in patients with PD. The aim of this systematic review was to put the spotlight on neuroimaging of the limbic system in PD and to give an overview of the most important structures affected by the disease, their function, disease related alterations, and corresponding clinical manifestations. PubMed was searched in order to identify the most recent studies that investigate the limbic system in PD with the help of neuroimaging methods. First, PD related neuropathological changes and corresponding clinical symptoms of each limbic system region are reviewed, and, finally, a network integration of the limbic system within the complex of PD pathology is discussed.

A causal role for the human subthalamic nucleus in non-selective cortico-motor inhibition

Common cortico-basal ganglia models of motor control suggest a key role for the subthalamic nucleus (STN) in motor inhibition.1-3 In particular, when already-initiated actions have to be suddenly stopped, the STN is purportedly recruited via a hyperdirect pathway to net inhibit the cortico-motor system in a broad, non-selective fashion.4 Indeed, the suppression of cortico-spinal excitability (CSE) during rapid action stopping extends beyond the stopped muscle and affects even task-irrelevant motor representations.5,6 Although such non-selective CSE suppression has long been attributed to the broad inhibitory influence of STN on the motor system, causal evidence for this association is hitherto lacking. Here, 20 Parkinson's disease patients treated with STN deep-brain stimulation (DBS) and 20 matched healthy controls performed a verbal stop-signal task while CSE was measured from a task-unrelated hand muscle. DBS allowed a causal manipulation of STN, while CSE was measured using transcranial magnetic stimulation (TMS) over primary motor cortex and concurrent electromyography. In patients OFF-DBS and controls, the CSE of the hand was non-selectively suppressed when the verbal response was successfully stopped. Crucially, this effect disappeared when STN was disrupted via DBS in the patient group. Using this unique combination of DBS and TMS during human behavior, the current study provides first causal evidence that STN is likely involved in non-selectively suppressing the physiological excitability of the cortico-motor system during action stopping. This confirms a core prediction of long-held cortico-basal ganglia circuit models of movement. The absence of cortico-motor inhibition during STN-DBS may also provide potential insights into the common side effects of STN-DBS, such as increased impulsivity.7-11.

Linking profiles of pathway activation with clinical motor improvements - A retrospective computational study

BACKGROUND

Deep brain stimulation (DBS) is an established therapy for patients with Parkinson's disease. In silico computer models for DBS hold the potential to inform a selection of stimulation parameters. In recent years, the focus has shifted towards DBS-induced firing in myelinated axons, deemed particularly relevant for the external modulation of neural activity.

OBJECTIVE

The aim of this project was to investigate correlations between patient-specific pathway activation profiles and clinical motor improvement.

METHODS

We used the concept of pathway activation modeling, which incorporates advanced volume conductor models and anatomically authentic fiber trajectories to estimate DBS-induced action potential initiation in anatomically plausible pathways that traverse in close proximity to targeted nuclei. We applied the method on two retrospective datasets of DBS patients, whose clinical improvement had been evaluated according to the motor part of the Unified Parkinson's Disease Rating Scale. Based on differences in outcome and activation levels for intrapatient DBS protocols in a training cohort, we derived a pathway activation profile that theoretically induces a complete alleviation of symptoms described by UPDRS-III. The profile was further enhanced by analyzing the importance of matching activation levels for individual pathways.

RESULTS

The obtained profile emphasized the importance of activation in pathways descending from the motor-relevant cortical regions as well as the pallidothalamic pathways. The degree of similarity of patient-specific profiles to the optimal profile significantly correlated with clinical motor improvement in a test cohort.

CONCLUSION

Pathway activation modeling has a translational utility in the context of motor symptom alleviation in Parkinson's patients treated with DBS.

Depression history modulates effects of subthalamic nucleus topography on neuropsychological outcomes of deep brain stimulation for Parkinson's disease

Patients with psychiatric symptoms, such as depression, anxiety, and visual hallucinations, may be at increased risk for adverse effects following deep brain stimulation of the subthalamic nucleus for Parkinson's disease, but there have been relatively few studies of associations between locations of chronic stimulation and neuropsychological outcomes. We sought to determine whether psychiatric history modulates associations between stimulation location within the subthalamic nucleus and postoperative affective and cognitive changes. We retrospectively identified 42 patients with Parkinson's disease who received bilateral subthalamic nucleus deep brain stimulation and who completed both pre- and postoperative neuropsychological testing. Active stimulation contacts were localized in MNI space using Lead-DBS software. Linear discriminant analysis identified vectors maximizing variance in postoperative neuropsychological changes, and Pearson's correlations were used to assess for linear relationships. Stimulation location was associated with postoperative change for only 3 of the 18 neuropsychological measures. Variation along the superioinferior (z) axis was most influential. Constraining the analysis to patients with a history of depression revealed 10 measures significantly associated with active contact location, primarily related to location along the anterioposterior (y) axis and with worse outcomes associated with more anterior stimulation. Analysis of patients with a history of anxiety revealed 5 measures with location-associated changes without a predominant axis. History of visual hallucinations was not associated with significant findings. Our results suggest that a history of depression may influence the relationship between active contact location and neuropsychological outcomes following subthalamic nucleus deep brain stimulation. These patients may be more sensitive to off-target (nonmotor) stimulation.

Effects of diffusion signal modeling and segmentation approaches on subthalamic nucleus parcellation

The subthalamic nucleus (STN) is commonly used as a surgical target for deep brain stimulation in movement disorders such as Parkinson's Disease. Tractography-derived connectivity-based parcellation (CBP) has been recently proposed as a suitable tool for non-invasive in vivo identification and pre-operative targeting of specific functional territories within the human STN. However, a well-established, accurate and reproducible protocol for STN parcellation is still lacking. The present work aims at testing the effects of different tractography-based approaches for the reconstruction of STN functional territories. We reconstructed functional territories of the STN on the high-quality dataset of 100 unrelated healthy subjects and on the test-retest dataset of the Human Connectome Project (HCP) repository. Connectivity-based parcellation was performed with a hypothesis-driven approach according to cortico-subthalamic connectivity, after dividing cortical areas into three groups: associative, limbic and sensorimotor. Four parcellation pipelines were compared, combining different signal modeling techniques (single-fiber vs multi-fiber) and different parcellation approaches (winner takes all parcellation vs fiber density thresholding). We tested these procedures on STN regions of interest obtained from three different, commonly employed, subcortical atlases. We evaluated the pipelines both in terms of between-subject similarity, assessed on the cohort of 100 unrelated healthy subjects, and of within-subject similarity, using a second cohort of 44 subjects with available test-retest data. We found that each parcellation provides converging results in terms of location of the identified parcels, but with significative variations in size and shape. All pipelines obtained very high within-subject similarity, with tensor-based approaches outperforming multi-fiber pipelines. On the other hand, higher between-subject similarity was found with multi-fiber signal modeling techniques combined with fiber density thresholding. We suggest that a fine-tuning of tractography-based parcellation may lead to higher reproducibility and aid the development of an optimized surgical targeting protocol.

Functional neuroanatomy of mania

Mania, the diagnostic hallmark of bipolar disorder, is an episodic disturbance of mood, sleep, behavior, and perception. Improved understanding of the neurobiology of mania is expected to allow for novel avenues to address current challenges in its diagnosis and treatment. Previous research focusing on the impairment of functional neuronal circuits and brain networks has resulted in heterogenous findings, possibly due to a focus on bipolar disorder and its several phases, rather than on the unique context of mania. Here we present a comprehensive overview of the evidence regarding the functional neuroanatomy of mania. Our interpretation of the best available evidence is consistent with a convergent model of lateralized circuit dysfunction in mania, with hypoactivity of the ventral prefrontal cortex in the right hemisphere, and hyperactivity of the amygdala, basal ganglia, and anterior cingulate cortex in the left hemisphere of the brain. Clarification of dysfunctional neuroanatomic substrates of mania may contribute not only to improve understanding of the neurobiology of bipolar disorder overall, but also highlights potential avenues for new circuit-based therapeutic approaches in the treatment of mania.

Functional correlates of response inhibition in impulse control disorders in Parkinson's disease

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PD patients with ICD behave like controls in proactive and reactive inhibition.

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PD patients with ICD recruit different mechanisms depending on the inhibition type.

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Proactive inhibition is executed hyperactivating the stopping network bilaterally.

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Restrained inhibition is accomplished with the coactivation of attentional areas.

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In restrained inhibition, connectivity between right STN and precuneus is reduced.

Impulse control disorder is a prevalent side-effect of Parkinson’s disease (PD) medication, with a strong negative impact on the quality of life of those affected. Although impulsivity has classically been associated with response inhibition deficits, previous evidence from PD patients with impulse control disorder (ICD) has not revealed behavioral dysfunction in response inhibition. In this study, 18 PD patients with ICD, 17 PD patients without this complication, and 15 healthy controls performed a version of the conditional Stop Signal Task during functional magnetic resonance imaging. Whole-brain contrasts, regions of interest, and functional connectivity analyses were conducted. Our aim was to investigate the neural underpinnings of two aspects of response inhibition: proactive inhibition, inhibition that has been prepared beforehand, and restrained inhibition, inhibition of an invalid inhibitory tendency. We observed that, in respect to the other two groups, PD patients with ICD exhibited hyperactivation of the stopping network bilaterally while performing proactive inhibition. When engaged in restrained inhibition, they showed hyperactivation of the left inferior frontal gyrus, an area linked to action monitoring. Restrained inhibition also resulted in changes to the functional co-activation between inhibitory regions and left inferior parietal cortex and right supramarginal gyrus. Our findings indicate that PD patients with ICD completed the inhibition task correctly, showing altered engagement of inhibitory and attentional areas. During proactive inhibition they showed bilateral hyperactivation of two inhibitory regions, while during restrained inhibition they showed additional involvement of attentional areas responsible for alerting and orienting.

Structural Connectivity of Subthalamic Nucleus Stimulation for Improving Freezing of Gait

BACKGROUND

Freezing of gait (FOG) is among the most common and disabling symptoms of Parkinson's disease (PD). Studies show that deep brain stimulation (DBS) of the subthalamic nucleus (STN) can reduce FOG severity. However, there is uncertainty about pathways that need to be modulated to improve FOG.

OBJECTIVE

To investigate whether STN-DBS effectively reduces FOG postoperatively and whether structural connectivity of the stimulated tissue explains variance of outcomes.

METHODS

We investigated 47 patients with PD and preoperative FOG. Freezing prevalence and severity was primarily assessed using the Freezing of Gait Questionnaire (FOG-Q). In a subset of 18 patients, provoked FOG during a standardized walking course was assessed. Using a publicly available model of basal-ganglia pathways we determined stimulation-dependent connectivity associated with postoperative changes in FOG. A region-of-interest analysis to a priori defined mesencephalic regions was performed using a disease-specific normative connectome.

RESULTS

Freezing of gait significantly improved six months postoperatively, marked by reduced frequency and duration of freezing episodes. Optimal stimulation volumes for improving FOG structurally connected to motor areas, the prefrontal cortex and to the globus pallidus. Stimulation of the lenticular fasciculus was associated with worsening of FOG. This connectivity profile was robust in a leave-one-out cross-validation. Subcortically, stimulation of fibers crossing the pedunculopontine nucleus and the substantia nigra correlated with postoperative improvement.

CONCLUSION

STN-DBS can alleviate FOG severity by modulating specific pathways structurally connected to prefrontal and motor cortices. More differentiated FOG assessments may allow to differentiate pathways for specific FOG subtypes in the future.

Deep brain stimulation effect on anterior pallidum reduces motor impulsivity in Parkinson's disease

BACKGROUND

Deep Brain Stimulation (DBS) of the subthalamic nucleus or globus pallidus internus is used to treat the motor symptoms of Parkinson's disease. The former can worsen impulsive and compulsive behaviors after controlling for the reduction of dopaminergic medications. However, the effect of pallidal DBS on such behaviors in PD patients is less clear.

OBJECTIVE/HYPOTHESIS

We hypothesized that greater stimulation spread to the pallidum with prefrontal connectivity would reduce motor impulsivity.

METHODS

Seven Parkinson's patients with stable globus pallidus internus DBS settings for 3 months, disease duration of 13 ± 1.3 years, and Montreal Cognitive Assessment of 26.8 ± 1.1 each had two stimulation settings defined based on reconstructions of lead placement and volume of tissue activation targeting either a dorsal or ventral position along the DBS electrode but still within the globus pallidus internus. Subjects performed a stop signal reaction time task with the DBS turned off vs. on in each of the defined stimulation settings, which was correlated with the degree of stimulation effect on pallidal subregions.

RESULTS

A shorter distance between the volume of tissue activation and the right prefrontally-connected GPi correlated with less impulsivity on the stop signal reaction time task (r = 0.69, p < 0.05). Greater volume of tissue activation overlap with the non-prefrontally-connected globus pallidus internus was associated with increased impulsivity.

CONCLUSION

These data can be leveraged to optimize DBS programming in PD patients with problematic impulsivity or in other disorders involving impulsive behaviors such as substance use disorders.

Toward personalized medicine in connectomic deep brain stimulation

At the group-level, deep brain stimulation leads to significant therapeutic benefit in a multitude of neurological and neuropsychiatric disorders. At the single-patient level, however, symptoms may sometimes persist despite "optimal" electrode placement at established treatment coordinates. This may be partly explained by limitations of disease-centric strategies that are unable to account for heterogeneous phenotypes and comorbidities observed in clinical practice. Instead, tailoring electrode placement and programming to individual patients' symptom profiles may increase the fraction of top-responding patients. Here, we propose a three-step, circuit-based framework with the aim of developing patient-specific treatment targets that address the unique symptom constellation prevalent in each patient. First, we describe how a symptom network target library could be established by mapping beneficial or undesirable DBS effects to distinct circuits based on (retrospective) group-level data. Second, we suggest ways of matching the resulting symptom networks to circuits defined in the individual patient (template matching). Third, we introduce network blending as a strategy to calculate optimal stimulation targets and parameters by selecting and weighting a set of symptom-specific networks based on the symptom profile and subjective priorities of the individual patient. We integrate the approach with published literature and conclude by discussing limitations and future challenges.

Clinical applications of magnetic resonance imaging based functional and structural connectivity

Advances in computational neuroimaging techniques have expanded the armamentarium of imaging tools available for clinical applications in clinical neuroscience. Non-invasive, in vivo brain MRI structural and functional network mapping has been used to identify therapeutic targets, define eloquent brain regions to preserve, and gain insight into pathological processes and treatments as well as prognostic biomarkers. These tools have the real potential to inform patient-specific treatment strategies. Nevertheless, a realistic appraisal of clinical utility is needed that balances the growing excitement and interest in the field with important limitations associated with these techniques. Quality of the raw data, minutiae of the processing methodology, and the statistical models applied can all impact on the results and their interpretation. A lack of standardization in data acquisition and processing has also resulted in issues with reproducibility. This limitation has had a direct impact on the reliability of these tools and ultimately, confidence in their clinical use. Advances in MRI technology and computational power as well as automation and standardization of processing methods, including machine learning approaches, may help address some of these issues and make these tools more reliable in clinical use. In this review, we will highlight the current clinical uses of MRI connectomics in the diagnosis and treatment of neurological disorders; balancing emerging applications and technologies with limitations of connectivity analytic approaches to present an encompassing and appropriate perspective.

Predictors of short-term impulsive and compulsive behaviour after subthalamic stimulation in Parkinson disease

BACKGROUND

The effects of subthalamic stimulation (subthalamic nucleus-deep brain stimulation, STN-DBS) on impulsive and compulsive behaviours (ICB) in Parkinson's disease (PD) are understudied.

OBJECTIVE

To investigate clinical predictors of STN-DBS effects on ICB.

METHODS

In this prospective, open-label, multicentre study in patients with PD undergoing bilateral STN-DBS, we assessed patients preoperatively and at 6-month follow-up postoperatively. Clinical scales included the Questionnaire for Impulsive-Compulsive Disorders in PD-Rating Scale (QUIP-RS), PD Questionnaire-8, Non-Motor Symptom Scale (NMSS), Unified PD Rating Scale in addition to levodopa-equivalent daily dose total (LEDD-total) and dopamine agonists (LEDD-DA). Changes at follow-up were analysed with Wilcoxon signed-rank test and corrected for multiple comparisons (Bonferroni method). We explored predictors of QUIP-RS changes using correlations and linear regressions. Finally, we dichotomised patients into 'QUIP-RS improvement or worsening' and analysed between-group differences.

RESULTS

We included 55 patients aged 61.7 years±8.4 with 9.8 years±4.6 PD duration. QUIP-RS cut-offs and psychiatric assessments identified patients with preoperative ICB. In patients with ICB, QUIP-RS improved significantly. However, we observed considerable interindividual variability of clinically relevant QUIP-RS outcomes as 27.3% experienced worsening and 29.1% an improvement. In post hoc analyses, higher baseline QUIP-RS and lower baseline LEDD-DA were associated with greater QUIP-RS improvements. Additionally, the 'QUIP-RS worsening' group had more severe baseline impairment in the NMSS attention/memory domain.

CONCLUSIONS

Our results show favourable ICB outcomes in patients with higher preoperative ICB severity and lower preoperative DA doses, and worse outcomes in patients with more severe baseline attention/memory deficits. These findings emphasise the need for comprehensive non-motor and motor symptoms assessments in patients undergoing STN-DBS.

TRIAL REGISTRATION NUMBER

DRKS00006735.

A Unified Functional Network Target for Deep Brain Stimulation in Obsessive-Compulsive Disorder

BACKGROUND

Multiple deep brain stimulation (DBS) targets have been proposed for treating intractable obsessive-compulsive disorder (OCD). Here, we investigated whether stimulation effects of different target sites would be mediated by one common or several segregated functional brain networks.

METHODS

First, seeding from active electrodes of 4 OCD patient cohorts (N = 50) receiving DBS to anterior limb of the internal capsule or subthalamic nucleus zones, optimal functional connectivity profiles for maximal Yale-Brown Obsessive Compulsive Scale improvements were calculated and cross-validated in leave-one-cohort-out and leave-one-patient-out designs. Second, we derived optimal target-specific connectivity patterns to determine brain regions mutually predictive of clinical outcome for both targets and others predictive for either target alone. Functional connectivity was defined using resting-state functional magnetic resonance imaging data acquired in 1000 healthy participants.

RESULTS

While optimal functional connectivity profiles showed both commonalities and differences between target sites, robust cross-predictions of clinical improvements across OCD cohorts and targets suggested a shared network. Connectivity to the anterior cingulate cortex, insula, and precuneus, among other regions, was predictive regardless of stimulation target. Regions with maximal connectivity to these commonly predictive areas included the insula, superior frontal gyrus, anterior cingulate cortex, and anterior thalamus, as well as the original stereotactic targets.

CONCLUSIONS

Pinpointing the network modulated by DBS for OCD from different target sites identified a set of brain regions to which DBS electrodes associated with optimal outcomes were functionally connected-regardless of target choice. On these grounds, we establish potential brain areas that could prospectively inform additional or alternative neuromodulation targets for obsessive-compulsive disorder.

Effect of deep brain stimulation on brain network and white matter integrity in Parkinson's disease

Aims

The effects of subthalamic nucleus (STN)‐deep brain stimulation (DBS) on brain topological metrics, functional connectivity (FC), and white matter integrity were studied in levodopa‐treated Parkinson’s disease (PD) patients before and after DBS.

Methods

Clinical assessment, resting‐state functional MRI (rs‐fMRI), and diffusion tensor imaging (DTI) were performed pre‐ and post‐DBS in 15 PD patients, using a within‐subject design. The rs‐fMRI identified brain network topological metric and FC changes using graph‐theory‐ and seed‐based methods. White matter integrity was determined by DTI and tract‐based spatial statistics.

Results

Unified Parkinson's Disease Rating Scale III (UPDRS‐ III) scores were significantly improved by 35.3% (p < 0.01) after DBS in PD patients, compared with pre‐DBS patients without medication. Post‐DBS PD patients showed a significant decrease in the graph‐theory‐based degree and cost in the middle temporal gyrus and temporo‐occipital part‐Right. Changes in FC were seen in four brain regions, and a decrease in white matter integrity was seen in the left anterior corona radiata. The topological metrics changes were correlated with Beck Depression Inventory II (BDI‐II) and the FC changes with UPDRS‐III scores.

Conclusion

STN‐DBS modulated graph‐theoretical metrics, FC, and white matter integrity. Brain connectivity changes observed with multi‐modal imaging were also associated with postoperative clinical improvement. These findings suggest that the effects of STN‐DBS are caused by brain network alterations.

Subthalamic and pallidal deep brain stimulation: are we modulating the same network?

The subthalamic nucleus and internal pallidum are main target sites for deep brain stimulation in Parkinson's disease. Multiple trials that investigated subthalamic versus pallidal stimulation were unable to settle on a definitive optimal target between the two. One reason could be that the effect is mediated via a common functional network. To test this hypothesis, we calculated connectivity profiles seeding from deep brain stimulation electrodes in 94 patients that underwent subthalamic and 28 patients with pallidal treatment based on a normative connectome atlas calculated from 1,000 healthy subjects. In each cohort, we calculated connectivity profiles that were associated with optimal clinical improvements. The two maps showed striking similarity and were able to cross-predict outcomes in the respective other cohort (R = 0.37 at p < 0.001; R = 0.34 at p = 0.032). Next, we calculated an agreement map which retained regions common to both target sites. Crucially, this map was able to explain an additional amount of variance in clinical improvements of either cohort when compared to the maps calculated on the two cohorts alone. Finally, we tested profiles and predictive utility of connectivity maps calculated from different motor symptom subscores with a specific focus on bradykinesia and rigidity. While our study is based on retrospective data and indirect connectivity metrics, it may deliver empirical data to support the hypothesis of a largely overlapping network associated with effective deep brain stimulation in Parkinson's disease irrespective of the specific target.

An active inference perspective on the negative symptoms of schizophrenia

Predictive coding has played a transformative role in the study of psychosis, casting delusions and hallucinations as statistical inference in a system with abnormal precision. However, the negative symptoms of schizophrenia, such as affective blunting, avolition, and asociality, remain poorly understood. We propose a computational framework for emotional expression based on active inference-namely that affective behaviours such as smiling are driven by predictions about the social consequences of smiling. Similarly to how delusions and hallucinations can be explained by predictive uncertainty in sensory circuits, negative symptoms naturally arise from uncertainty in social prediction circuits. This perspective draws on computational principles to explain blunted facial expressiveness and apathy-anhedonia in schizophrenia. Its phenomenological consequences also shed light on the content of paranoid delusions and indistinctness of self-other boundaries. Close links are highlighted between social prediction, facial affect mirroring, and the fledgling study of interoception. Advances in automated analysis of facial expressions and acoustic speech patterns will allow empirical testing of these computational models of the negative symptoms of schizophrenia.

Does Personality Change Follow Deep Brain Stimulation in Parkinson's Disease Patients?

Deep Brain Stimulation (DBS) has emerged as a safe, effective, and appealing treatment for Parkinson's Disease (PD), particularly for improving motor symptoms (e. g., tremor, bradykinesia, and rigidity). However, concerns have been raised about whether DBS causes psychological changes, including changes to personality: characteristic and relatively stable patterns of affect, behavior, cognition, and desire. In this article, after first presenting some background information about PD and DBS, we examined evidence obtained from various empirical research methods (quantitative, qualitative, and mixed methods for evaluating patient valued characteristics) pertaining to whether DBS causes personality change. General limitations across research methods include a lack of randomized clinical trials and small sample sizes. We organized our review of findings according to different layers of personality variables: dispositional traits (including personality pathology), characteristic adaptations, and narrative identity. Though most work has been done on dispositional traits, there is not much evidence that dispositional traits change following DBS. Little work has been done on characteristic adaptations, but there is somewhat consistent evidence for positive perceived progress toward goals across a number of domains: routine activities, work, social/relational, and leisure. Nascent work on narrative identity holds promise for revealing issues around self-image that may be common following DBS. We listed a number of strategies for advancing research, highlighting opportunities related to personality conceptualization, personality assessment, and interdisciplinary scholarship. Finally, we offer practical applications of our findings for the informed consent process and for ongoing treatment.

Triboelectric Nanogenerators for Therapeutic Electrical Stimulation

Current solutions developed for the purpose of in and on body (IOB) electrical stimulation (ES) lack autonomous qualities necessary for comfortable, practical, and self-dependent use. Consequently, recent focus has been placed on developing self-powered IOB therapeutic devices capable of generating therapeutic ES for human use. With the recent invention of the triboelectric nanogenerator (TENG), harnessing passive human biomechanical energy to develop self-powered systems has allowed for the introduction of novel therapeutic ES solutions. TENGs are especially effective at providing ES for IOB therapeutic systems given their bioconformability, low cost, simple manufacturability, and self-powering capabilities. Due to the key role of naturally induced electrical signals in many physiological functions, TENG-induced ES holds promise to provide a novel paradigm in therapeutic interventions. The aim here is to detail research on IOB TENG devices applied for ES-based therapy in the fields of regenerative medicine, neurology, rehabilitation, and pharmaceutical engineering. Furthermore, considering TENG-produced ES can be measured for sensing applications, this technology is paving the way to provide a fully autonomous personalized healthcare system, capable of IOB energy generation, sensing, and therapeutic intervention. Considering these grounds, it seems highly relevant to review TENG-ES research and applications, as they could constitute the foundation and future of personalized healthcare.

Neurophysiological Correlates of Trait Impulsivity in Parkinson's Disease

Background

Impulsivity is common in people with Parkinson’s disease (PD), with many developing impulsive compulsive behavior disorders (ICB). Its pathophysiological basis remains unclear.

Objectives

We aimed to investigate local field potential (LFP) markers of trait impulsivity in PD and their relationship to ICB.

Methods

We recorded subthalamic nucleus (STN) LFPs in 23 PD patients undergoing deep brain stimulation implantation. Presence and severity of ICB were assessed by clinical interview and the Questionnaire for Impulsive-Compulsive Disorders in PD-Rating Scale (QUIP-RS), whereas trait impulsivity was estimated with the Barratt Impulsivity Scale (BIS-11). Recordings were obtained during the off dopaminergic states and the power spectrum of the subthalamic activity was analyzed using Fourier transform-based techniques. Assessment of each electrode contact localization was done to determine the topography of the oscillatory activity recorded.

Results

Patients with (n = 6) and without (n = 17) ICB had similar LFP spectra. A multiple regression model including QUIP-RS, BIS-11, and Unified PD Rating Scale-III scores as regressors showed a significant positive correlation between 8–13 Hz power and BIS-11 score. The correlation was mainly driven by the motor factor of the BIS-11, and was irrespective of the presence or absence of active ICB. Electrode contact pairs with the highest α power, which also correlated most strongly with BIS-11, tended to be more ventral than contact pairs with the highest beta power, which localize to the dorsolateral motor STN.

Conclusions

Our data suggest a link between α power and trait impulsivity in PD, irrespective of the presence and severity of ICB.

Neuropsychiatric Symptoms in Parkinson's Disease After Subthalamic Nucleus Deep Brain Stimulation

Background: Indications for subthalamic nucleus deep brain stimulation (STN-DBS) surgery are determined basically by preoperative motor function; however, postoperative quality of life (QOL) is not necessarily associated with improvements in motor symptoms, suggesting that neuropsychiatric symptoms might be related to QOL after surgery in patients with Parkinson's disease.

Objectives: We aimed to examine temporal changes in neuropsychiatric symptoms and their associations with QOL after STN-DBS.

Materials and Methods: We prospectively enrolled a total of 61 patients with Parkinson's disease (mean age = 65.3 ± 0.9 years, mean disease duration = 11.9 ± 0.4 years). Motor function, cognitive function, and neuropsychiatric symptoms were evaluated before and after DBS surgery. Postoperative evaluation was performed at 3 months, 1 year, and 3 years after surgery.

Results: Of the 61 participants, 54 completed postoperative clinical evaluation after 3 months, 47 after 1 year, and 23 after 3 years. Frontal lobe functions, depression, and verbal fluency significantly worsened 3 years after STN-DBS. Non-motor symptoms such as impulsivity and the Unified PD Rating Scale (UPDRS) part I score were associated with QOL after STN-DBS.

Conclusions: Frontal lobe functions, depression, and verbal fluency significantly worsened 3 years after STN-DBS. The UPDRS part I score and higher impulsivity might be associated with QOL after STN-DBS.

A randomised, double-blind, sham-controlled trial of deep brain stimulation of the bed nucleus of the stria terminalis for treatment-resistant obsessive-compulsive disorder

Deep brain stimulation (DBS) is a promising treatment for severe, treatment-resistant obsessive-compulsive disorder (OCD). Here, nine participants (four females, mean age 47.9 ± 10.7 years) were implanted with DBS electrodes bilaterally in the bed nucleus of the stria terminalis (BNST). Following a one-month postoperative recovery phase, participants entered a three-month randomised, double-blind, sham-controlled phase before a twelve-month period of open-label stimulation incorporating a course of cognitive behavioural therapy (CBT). The primary outcome measure was OCD symptoms as rated with the Yale-Brown Obsessive-Compulsive Scale (YBOCS). In the blinded phase, there was a significant benefit of active stimulation over sham (p = 0.025, mean difference 4.9 points). After the open phase, the mean reduction in YBOCS was 16.6 ± 1.9 points (χ² (11) = 39.8, p = 3.8 × 10^-5), with seven participants classified as responders. CBT resulted in an additive YBOCS reduction of 4.8 ± 3.9 points (p = 0.011). There were two serious adverse events related to the DBS device, the most severe of which was an infection during the open phase necessitating device explantation. There were no serious psychiatric adverse events related to stimulation. An analysis of the structural connectivity of each participant's individualised stimulation field isolated right-hemispheric fibres associated with YBOCS reduction. These included subcortical tracts incorporating the amygdala, hippocampus and stria terminalis, in addition to cortical regions in the ventrolateral and ventromedial prefrontal cortex, parahippocampal, parietal and extrastriate visual cortex. In conclusion, this study provides further evidence supporting the efficacy and tolerability of DBS in the region of the BNST for individuals with otherwise treatment-refractory OCD and identifies a connectivity fingerprint associated with clinical benefit.

GABAergic cortical network physiology in frontotemporal lobar degeneration

The clinical syndromes caused by frontotemporal lobar degeneration are heterogeneous, including the behavioural variant frontotemporal dementia (bvFTD) and progressive supranuclear palsy. Although pathologically distinct, they share many behavioural, cognitive and physiological features, which may in part arise from common deficits of major neurotransmitters such as γ-aminobutyric acid (GABA). Here, we quantify the GABAergic impairment and its restoration with dynamic causal modelling of a double-blind placebo-controlled crossover pharmaco-magnetoencephalography study. We analysed 17 patients with bvFTD, 15 patients with progressive supranuclear palsy, and 20 healthy age- and gender-matched controls. In addition to neuropsychological assessment and structural MRI, participants undertook two magnetoencephalography sessions using a roving auditory oddball paradigm: once on placebo and once on 10 mg of the oral GABA reuptake inhibitor tiagabine. A subgroup underwent ultrahigh-field magnetic resonance spectroscopy measurement of GABA concentration, which was reduced among patients. We identified deficits in frontotemporal processing using conductance-based biophysical models of local and global neuronal networks. The clinical relevance of this physiological deficit is indicated by the correlation between top-down connectivity from frontal to temporal cortex and clinical measures of cognitive and behavioural change. A critical validation of the biophysical modelling approach was evidence from parametric empirical Bayes analysis that GABA levels in patients, measured by spectroscopy, were related to posterior estimates of patients’ GABAergic synaptic connectivity. Further evidence for the role of GABA in frontotemporal lobar degeneration came from confirmation that the effects of tiagabine on local circuits depended not only on participant group, but also on individual baseline GABA levels. Specifically, the phasic inhibition of deep cortico-cortical pyramidal neurons following tiagabine, but not placebo, was a function of GABA concentration. The study provides proof-of-concept for the potential of dynamic causal modelling to elucidate mechanisms of human neurodegenerative disease, and explains the variation in response to candidate therapies among patients. The laminar- and neurotransmitter-specific features of the modelling framework, can be used to study other treatment approaches and disorders. In the context of frontotemporal lobar degeneration, we suggest that neurophysiological restoration in selected patients, by targeting neurotransmitter deficits, could be used to bridge between clinical and preclinical models of disease, and inform the personalized selection of drugs and stratification of patients for future clinical trials.

Impact of deep brain stimulation of the subthalamic nucleus on natural language in patients with Parkinson's disease

Background

In addition to the typical motor symptoms, a majority of patients suffering from Parkinson’s disease experience language impairments. Deep Brain Stimulation of the subthalamic nucleus robustly reduces motor dysfunction, but its impact on language skills remains ambiguous.

Method

To elucidate the impact of subthalamic deep brain stimulation on natural language production, we systematically analyzed language samples from fourteen individuals (three female / eleven male, average age 66.43 ± 7.53 years) with Parkinson’s disease in the active (ON) versus inactive (OFF) stimulation condition. Significant ON-OFF differences were considered as stimulation effects. To localize their neuroanatomical origin within the subthalamic nucleus, they were correlated with the volume of tissue activated by therapeutic stimulation.

Results

Word and clause production speed increased significantly under active stimulation. These enhancements correlated with the volume of tissue activated within the associative part of the subthalamic nucleus, but not with that within the dorsolateral motor part, which again correlated with motor improvement. Language error rates were lower in the ON vs. OFF condition, but did not correlate with electrode localization. No significant changes in further semantic or syntactic language features were detected in the current study.

Conclusion

The findings point towards a facilitation of executive language functions occurring rather independently from motor improvement. Given the presumed origin of this stimulation effect within the associative part of the subthalamic nucleus, this could be due to co-stimulation of the prefrontal-subthalamic circuit.

Probabilistic Mapping of Deep Brain Stimulation: Insights from 15 Years of Therapy

Deep brain stimulation (DBS) depends on precise delivery of electrical current to target tissues. However, the specific brain structures responsible for best outcome are still debated. We applied probabilistic stimulation mapping to a retrospective, multidisorder DBS dataset assembled over 15 years at our institution (n_total = 482 patients; n_{Parkinson disease} = 303; n_dystonia = 64; n_tremor = 39; n_{treatment-resistant depression/anorexia nervosa} = 76) to identify the neuroanatomical substrates of optimal clinical response. Using high-resolution structural magnetic resonance imaging and activation volume modeling, probabilistic stimulation maps (PSMs) that delineated areas of above-mean and below-mean response for each patient cohort were generated and defined in terms of their relationships with surrounding anatomical structures. Our results show that overlap between PSMs and individual patients' activation volumes can serve as a guide to predict clinical outcomes, but that this is not the sole determinant of response. In the future, individualized models that incorporate advancements in mapping techniques with patient-specific clinical variables will likely contribute to the optimization of DBS target selection and improved outcomes for patients. ANN NEUROL 2021;89:426-443.

Opportunities of connectomic neuromodulation

The process of altering neural activity - neuromodulation - has long been used to treat patients with brain disorders and answer scientific questions. Deep brain stimulation in particular has provided clinical benefit to over 150,000 patients. However, our understanding of how neuromodulation impacts the brain is evolving. Instead of focusing on the local impact at the stimulation site itself, we are considering the remote impact on brain regions connected to the stimulation site. Brain connectivity information derived from advanced magnetic resonance imaging data can be used to identify these connections and better understand clinical and behavioral effects of neuromodulation. In this article, we review studies combining neuromodulation and brain connectomics, highlighting opportunities where this approach may prove particularly valuable. We focus on deep brain stimulation, but show that the same principles can be applied to other forms of neuromodulation, such as transcranial magnetic stimulation and MRI-guided focused ultrasound. We outline future perspectives and provide testable hypotheses for future work.

Mapping the hyper-direct circuitry of impulsivity

This scientific commentary refers to ‘The structural connectivity of subthalamic deep brain stimulation correlates with impulsivity in Parkinson’s’, by Mosley et al. (doi:10.1093/brain/awaa148).