Subthalamic stimulation impairs stopping of ongoing movements

Cortico-striatal gamma oscillations are modulated by dopamine D3 receptors in dyskinetic rats

JOURNAL/nrgr/04.03/01300535-202504000-00031/figure1/v/2024-07-06T104127Z/r/image-tiff Long-term levodopa administration can lead to the development of levodopa-induced dyskinesia. Gamma oscillations are a widely recognized hallmark of abnormal neural electrical activity in levodopa-induced dyskinesia. Currently, studies have reported increased oscillation power in cases of levodopa-induced dyskinesia. However, little is known about how the other electrophysiological parameters of gamma oscillations are altered in levodopa-induced dyskinesia. Furthermore, the role of the dopamine D3 receptor, which is implicated in levodopa-induced dyskinesia, in movement disorder-related changes in neural oscillations is unclear. We found that the cortico-striatal functional connectivity of beta oscillations was enhanced in a model of Parkinson's disease. Furthermore, levodopa application enhanced cortical gamma oscillations in cortico-striatal projections and cortical gamma aperiodic components, as well as bidirectional primary motor cortex (M1) ↔ dorsolateral striatum gamma flow. Administration of PD128907 (a selective dopamine D3 receptor agonist) induced dyskinesia and excessive gamma oscillations with a bidirectional M1 ↔ dorsolateral striatum flow. However, administration of PG01037 (a selective dopamine D3 receptor antagonist) attenuated dyskinesia, suppressed gamma oscillations and cortical gamma aperiodic components, and decreased gamma causality in the M1 → dorsolateral striatum direction. These findings suggest that the dopamine D3 receptor plays a role in dyskinesia-related oscillatory activity, and that it has potential as a therapeutic target for levodopa-induced dyskinesia.

Subthalamic DBS does not restore deficits in corticospinal suppression during movement preparation in Parkinson's disease

OBJECTIVE

Parkinson's disease (PD) patients exhibit changes in mechanisms underlying movement preparation, particularly the suppression of corticospinal excitability - termed "preparatory suppression" - which is thought to facilitate movement execution in healthy individuals. Deep brain stimulation (DBS) of the subthalamic nucleus (STN) being an attractive treatment for advanced PD, we aimed to study the potential contribution of this nucleus to PD-related changes in such corticospinal dynamics.

METHODS

On two consecutive days, we applied single-pulse transcranial magnetic stimulation to the primary motor cortex of 20 advanced PD patients treated with bilateral STN-DBS (ON vs. OFF), as well as 20 healthy control subjects. Motor-evoked potentials (MEPs) were elicited at rest or during movement preparation in an instructed-delay choice reaction time task including left- or right-hand responses. Preparatory suppression was assessed by expressing MEPs during movement preparation relative to rest.

RESULTS

PD patients exhibited a deficit in preparatory suppression when it was probed on the responding hand side, particularly when this corresponded to their most-affected hand, regardless of their STN-DBS status.

CONCLUSIONS

Advanced PD patients displayed a reduction in preparatory suppression which was not restored by STN-DBS.

SIGNIFICANCE

The current findings confirm that PD patients lack preparatory suppression, as previously reported. Yet, the fact that this deficit was not responsive to STN-DBS calls for future studies on the neural source of this regulatory mechanism during movement preparation.

Noninvasive intervention by transcranial ultrasound stimulation: Modulation of neural circuits and its clinical perspectives

Low-intensity focused transcranial ultrasound stimulation (TUS) is an emerging noninvasive technique capable of stimulating both the cerebral cortex and deep brain structures with high spatial precision. This method is recognized for its potential to comprehensively perturb various brain regions, enabling the modulation of neural circuits, in a manner not achievable through conventional magnetic or electrical brain stimulation techniques. The underlying mechanisms of neuromodulation are based on a phenomenon where mechanical waves of ultrasound kinetically interact with neurons, specifically affecting neuronal membranes and mechanosensitive channels. This interaction induces alterations in the excitability of neurons within the stimulated region. In this review, we briefly present the fundamental principles of ultrasound physics and the physiological mechanisms of TUS neuromodulation. We explain the experimental apparatus and procedures for TUS in humans. Due to the focality, the integration of various methods, including magnetic resonance imaging and magnetic resonance-guided neuronavigation systems, is important to perform TUS experiments for precise targeting. We then review the current state of the literature on TUS neuromodulation, with a particular focus on human subjects, targeting both the cerebral cortex and deep subcortical structures. Finally, we outline future perspectives of TUS in clinical applications in psychiatric and neurological fields.

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.

Modulation of subthalamic beta oscillations by movement, dopamine, and deep brain stimulation in Parkinson's disease

Subthalamic beta band activity (13-35 Hz) is known as a real-time correlate of motor symptom severity in Parkinson's disease (PD) and is currently explored as a feedback signal for closed-loop deep brain stimulation (DBS). Here, we investigate the interaction of movement, dopaminergic medication, and deep brain stimulation on subthalamic beta activity in PD patients implanted with sensing-enabled, implantable pulse generators. We recorded subthalamic activity from seven PD patients at rest and during repetitive movements in four conditions: after withdrawal of dopaminergic medication and DBS, with medication only, with DBS only, and with simultaneous medication and DBS. Medication and DBS showed additive effects in improving motor performance. Distinct effects of each therapy were seen in subthalamic recordings, with medication primarily suppressing low beta activity (13-20 Hz) and DBS being associated with a broad decrease in beta band activity (13-35 Hz). Movement suppressed beta band activity compared to rest. This suppression was most prominent when combining medication with DBS and correlated with motor improvement within patients. We conclude that DBS and medication have distinct effects on subthalamic beta activity during both rest and movement, which might explain their additive clinical effects as well as their difference in side-effect profiles. Importantly, subthalamic beta activity significantly correlated with motor symptoms across all conditions, highlighting its validity as a feedback signal for closed-loop DBS.

Structural connectivity of low-frequency subthalamic stimulation for improving stride length in Parkinson's disease

BACKGROUND

A reduction in stride length is considered a key characteristic of gait kinematics in Parkinson's disease (PD) and has been identified as a predictor of falls. Although low-frequency stimulation (LFS) has been suggested as a method to improve gait characteristics, the underlying structural network is not well understood.

OBJECTIVE

This study aims to investigate the structural correlates of changes in stride length during LFS (85 Hz).

METHODS

Objective gait performance was retrospectively evaluated in 19 PD patients who underwent deep brain stimulation (DBS) at 85 Hz and 130 Hz. Individual DBS contacts and volumes of activated tissue (VAT) were computed using preoperative magnetic resonance imaging (MRI) and postoperative computed tomography (CT) scans. Structural connectivity profiles to predetermined cortical and mesencephalic areas were estimated using a normative connectome.

RESULTS

LFS led to a significant improvement in stride length compared to 130 Hz stimulation. The intersection between VAT and the associative subregion of the subthalamic nucleus (STN) was associated with an improvement in stride length and had structural connections to the supplementary motor area, prefrontal cortex, and pedunculopontine nucleus. Conversely, we found that a lack of improvement was linked to stimulation volumes connected to cortico-diencephalic fibers bypassing the STN dorsolaterally. The robustness of the connectivity model was verified through leave-one-patient-out, 5-, and 10-fold cross cross-validation paradigms.

CONCLUSION

These findings offer new insights into the structural connectivity that underlies gait changes following LFS. Targeting the non-motor subregion of the STN with LFS on an individual level may present a potential therapeutic approach for PD patients with gait disorders.

Insights and opportunities for deep brain stimulation as a brain circuit intervention

Deep brain stimulation (DBS) is an effective treatment and has provided unique insights into the dynamic circuit architecture of brain disorders. This Review illustrates our current understanding of the pathophysiology of movement disorders and their underlying brain circuits that are modulated with DBS. It proposes principles of pathological network synchronization patterns like beta activity (13-35 Hz) in Parkinson's disease. We describe alterations from microscale including local synaptic activity via modulation of mesoscale hypersynchronization to changes in whole-brain macroscale connectivity. Finally, an outlook on advances for clinical innovations in next-generation neurotechnology is provided: from preoperative connectomic targeting to feedback controlled closed-loop adaptive DBS as individualized network-specific brain circuit interventions.

Subthalamic beta bursts correlate with dopamine-dependent motor symptoms in 106 Parkinson's patients

Pathologically increased beta power has been described as a biomarker for Parkinson's disease (PD) and related to prolonged bursts of subthalamic beta synchronization. Here, we investigate the association between subthalamic beta dynamics and motor impairment in a cohort of 106 Parkinson's patients in the ON- and OFF-medication state, using two different methods of beta burst determination. We report a frequency-specific correlation of low beta power and burst duration with motor impairment OFF dopaminergic medication. Furthermore, reduction of power and burst duration correlated significantly with symptom alleviation through dopaminergic medication. Importantly, qualitatively similar results were yielded with two different methods of beta burst definition. Our findings validate the robustness of previous results on pathological changes in subcortical oscillations both in the frequency- as well as in the time-domain in the largest cohort of PD patients to date with important implications for next-generation adaptive deep brain stimulation control algorithms.

Stimulation of non-motor subthalamic nucleus impairs selective response inhibition via prefrontal connectivity

Given the inconsistent results in the past, there is an ongoing debate whether and how deep brain stimulation in the subthalamic nucleus modifies cognitive control processes like response inhibition in persons with Parkinson's disease. In this study, we examined how the location of the stimulation volume within the subthalamic nucleus affects the performance in an antisaccade task but also how its structural connectivity is related to response inhibition. Antisaccade error rates and latencies were collected in 14 participants on and off deep brain stimulation in a randomized order. Stimulation volumes were computed based on patient-specific lead localizations using preoperative MRI and postoperative CT scans. Structural connectivity of the stimulation volumes with pre-defined cortical oculomotor control regions as well as whole-brain connectivity was estimated using a normative connectome. We showed that the detrimental effect of deep brain stimulation on response inhibition, measured as antisaccade error rate, depended upon the magnitude of the intersection of volumes of activated tissue with the non-motor subregion of the subthalamic nucleus and on its structural connectivity with regions of the prefrontal oculomotor network including bilateral frontal eye fields and right anterior cingulate cortex. Our results corroborate previous recommendations for avoidance of stimulation in the ventromedial non-motor subregion of the subthalamic nucleus which connects to the prefrontal cortex to prevent stimulation-induced impulsivity. Furthermore, antisaccades were initiated faster with deep brain stimulation when the stimulation volume was connected to fibres passing the subthalamic nucleus laterally and projecting onto the prefrontal cortex, indicating that improvement of voluntary saccade generation with deep brain stimulation may be an off-target effect driven by stimulation of corticotectal fibres directly projecting from the frontal and supplementary eye fields onto brainstem gaze control areas. Taken together, these findings could help implement individualized circuit-based deep brain stimulation strategies that avoid impulsive side effects while improving voluntary oculomotor control.

Altered dynamic functional network connectivity in levodopa-induced dyskinesia of Parkinson's disease

AIMS

The aim of this study was to clarify the dynamic neural activity of levodopa-induced dyskinesia (LID) in Parkinson's disease (PD).

METHODS

Using dynamic functional network connectivity (dFNC) analysis, we evaluated 41 PD patients with LID (LID group) and 34 PD patients without LID (No-LID group). Group spatial independent component analysis and sliding-window approach were employed. Moreover, we applied a k-means clustering algorithm on windowed functional connectivity (FC) matrices to identify reoccurring FC patterns (i.e., states).

RESULTS

The optimal number of states was determined to be five, the so-called State 1, 2, 3, 4, and 5. In ON phase, compared with No-LID group, LID group occurred more frequently and dwelled longer in strongly connected State 1, characterized by strong positive connections between visual network (VIS) and sensorimotor network (SMN). When switching from OFF to ON phase, LID group occurred less frequently in State 3 and State 4. Meanwhile, LID group dwelled longer in State 2 and shorter in State 3. No-LID group occurred more frequently in State 5 and less frequently in State 3. Additionally, correlation analysis demonstrated that dyskinesia's severity was associated with frequency of occurrence and dwell time in State 2, dominated by inferior frontal cortex in cognitive executive network (CEN).

CONCLUSION

Using dFNC analysis, we found that dyskinesia may be related to the dysfunctional inhibition of CEN on motor loops and excessive excitation of VIS and SMN, which provided evidence of the changes in brain dynamics associated with the occurrence of dyskinesia.

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.

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.

A causal role of anterior prefrontal-putamen circuit for response inhibition revealed by transcranial ultrasound stimulation in humans

Stopping an inappropriate response requires the involvement of the prefrontal-subthalamic hyperdirect pathway. However, how the prefrontal-striatal indirect pathway contributes to stopping is poorly understood. In this study, transcranial ultrasound stimulation is used to perform interventions in a task-related region in the striatum. Functional magnetic resonance imaging (MRI) reveals activation in the right anterior part of the putamen during response inhibition, and ultrasound stimulation to the anterior putamen, as well as the subthalamic nucleus, results in significant impairments in stopping performance. Diffusion imaging further reveals prominent structural connections between the anterior putamen and the right anterior part of the inferior frontal cortex (IFC), and ultrasound stimulation to the anterior IFC also shows significant impaired stopping performance. These results demonstrate that the right anterior putamen and right anterior IFC causally contribute to stopping and suggest that the anterior IFC-anterior putamen circuit in the indirect pathway serves as an essential route for stopping.

Electrocorticography is superior to subthalamic local field potentials for movement decoding in Parkinson's disease

Brain signal decoding promises significant advances in the development of clinical brain computer interfaces (BCI). In Parkinson's disease (PD), first bidirectional BCI implants for adaptive deep brain stimulation (DBS) are now available. Brain signal decoding can extend the clinical utility of adaptive DBS but the impact of neural source, computational methods and PD pathophysiology on decoding performance are unknown. This represents an unmet need for the development of future neurotechnology. To address this, we developed an invasive brain-signal decoding approach based on intraoperative sensorimotor electrocorticography (ECoG) and subthalamic LFP to predict grip-force, a representative movement decoding application, in 11 PD patients undergoing DBS. We demonstrate that ECoG is superior to subthalamic LFP for accurate grip-force decoding. Gradient boosted decision trees (XGBOOST) outperformed other model architectures. ECoG based decoding performance negatively correlated with motor impairment, which could be attributed to subthalamic beta bursts in the motor preparation and movement period. This highlights the impact of PD pathophysiology on the neural capacity to encode movement vigor. Finally, we developed a connectomic analysis that could predict grip-force decoding performance of individual ECoG channels across patients by using their connectomic fingerprints. Our study provides a neurophysiological and computational framework for invasive brain signal decoding to aid the development of an individualized precision-medicine approach to intelligent adaptive DBS.

Hold your horses: Differences in EEG correlates of inhibition in cancelling and stopping an action

Behavioral adaptation to changing contextual contingencies often requires the rapid inhibition of planned or ongoing actions. Inhibitory control has been mostly studied using the stop-signal paradigm, which conceptualizes action inhibition as the outcome of a race between independent GO and STOP processes. Inhibition is predominantly considered to be independent of action type, yet it is questionable whether this conceptualization can apply to stopping an ongoing action. To test the claimed generality of action inhibition, we investigated behavioral stop-signal reaction time (SSRT) and scalp electroencephalographic (EEG) activity in two inhibition contexts: Using variants of the stop-signal task, we asked participants to cancel a prepared-discrete action or to stop an ongoing-rhythmic action in reaction to a STOP signal. The behavioral analysis revealed that the discrete and rhythmic SSRTs were not correlated. The EEG analysis showed that the STOP signal evoked frontocentral activity in the time and frequency domains (Delta/Theta range) in a task-specific manner: The P3 onset latency was the best correlate of discrete SSRT whereas N2/P3 peak-to-peak amplitude was the best correlate of rhythmic SSRT. These findings do not support a conceptualization of inhibition as action-independent but rather suggest that the differential engagement of both components of the N2/P3-complex as a function of action type pertains to functionally independent inhibition subprocesses.

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.

Cortical sensorimotor activity in the execution and suppression of discrete and rhythmic movements

Although the engagement of sensorimotor cortices in movement is well documented, the functional relevance of brain activity patterns remains ambiguous. Especially, the cortical engagement specific to the pre-, within-, and post-movement periods is poorly understood. The present study addressed this issue by examining sensorimotor EEG activity during the performance as well as STOP-signal cued suppression of movements pertaining to two distinct classes, namely, discrete vs. ongoing rhythmic movements. Our findings indicate that the lateralized readiness potential (LRP), which is classically used as a marker of pre-movement processing, indexes multiple pre- and in- movement-related brain dynamics in a movement-class dependent fashion. In- and post-movement event-related (de)synchronization (ERD/ERS) observed in the Mu (8-13 Hz) and Beta (15-30 Hz) frequency ranges were associated with estimated brain sources in both motor and somatosensory cortical areas. Notwithstanding, Beta ERS occurred earlier following cancelled than actually performed movements. In contrast, Mu power did not vary. Whereas Beta power may reflect the evaluation of the sensory predicted outcome, Mu power might engage in linking perception to action. Additionally, the rhythmic movement forced stop (only) showed a post-movement Mu/Beta rebound, which might reflect an active "clearing-out" of the motor plan and its feedback-based online control. Overall, the present study supports the notion that sensorimotor EEG modulations are key markers to investigate control or executive processes, here initiation and inhibition, which are exerted when performing distinct movement classes.

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.

Multiple Brain Sources Are Differentially Engaged in the Inhibition of Distinct Action Types

Most studies contributing to identify the brain network for inhibitory control have investigated the cancelation of prepared-discrete actions, thus focusing on an isolated and short-lived chunk of human behavior. Aborting ongoing-continuous actions is an equally crucial ability but remains little explored. Although discrete and ongoing-continuous rhythmic actions are associated with partially overlapping yet largely distinct brain activations, it is unknown whether the inhibitory network operates similarly in both situations. Thus, distinguishing between action types constitutes a powerful means to investigate whether inhibition is a generic function. We, therefore, used independent component analysis (ICA) of EEG data and show that canceling a discrete action and aborting a rhythmic action rely on independent brain components. The ICA showed that a delta/theta power increase generically indexed inhibitory activity, whereas N2 and P3 ERP waves did so in an action-specific fashion. The action-specific components were generated by partially distinct brain sources, which indicates that the inhibitory network is engaged differently when canceling a prepared-discrete action versus aborting an ongoing-continuous action. In particular, increased activity was estimated in precentral gyri and posterior parts of the cingulate cortex for action canceling, whereas an enhanced activity was found in more frontal gyri and anterior parts of the cingulate cortex for action aborting. Overall, the present findings support the idea that inhibitory control is differentially implemented according to the type of action to revise.

Inter-individual performance differences in the stop-signal task are associated with fibre-specific microstructure of the fronto-basal-ganglia circuit in healthy children

Previous Diffusion Tensor Imaging (DTI) studies in children suggest that developmental improvements in inhibitory control is largely mediated by the degree of white matter organisation within a right-lateralised network of fronto-basal-ganglia regions. Recent advances in diffusion imaging analysis now permit greater biological specificity, both in identifying specific fibre populations within a voxel, as well as in the underlying microstructural properties of that white matter. In the present work, employing a novel fixel-based analysis (FBA) framework, we aimed to comprehensively investigate microstructure within the fronto-basal-ganglia circuit in childhood, and its contribution to inhibition performance. Diffusion MRI data were obtained from 43 healthy children and adolescents aged 9-11 years (10.42 ± .41 years, 18 females). Response inhibition for each participant was assessed using the Stop-signal Task (SST) and quantified as a Stop-Signal Reaction Time (SSRT). All steps relevant to FBA were implemented in MRtrix3Tissue, a fork of the MRtrix3 software library. The fronto-basal-ganglia circuit were delineated using probabilistic tractography to identify the tracts connecting the subthalamic nucleus, pre-supplementary motor area and the inferior frontal gyrus. Connectivity-based fixel enhancement (CFE) was then used to assess the association between fibre density (FD) and fibre cross-section (FC) with inhibitory ability. Significant negative associations were identified for FD in both the right and left fronto-basal-ganglia circuit whereby greater FD was associated with better inhibition performance (e.g., reduced SSRTs). This effect was specifically localised to clusters of fixels within white matter proximal to the right subthalamic nucleus. We did not report any meaningful associations between SSRT and FC. Whilst findings are broadly consistent with prior DTI evidence, current results suggest that SSRT is predominantly facilitated by subcortical microstructure of the connections projecting from the subthalamic nucleus to the cortical regions of the network. Our findings extend current understanding of the role of white matter in childhood response inhibition.

Proactive inhibition is not modified by deep brain stimulation for Parkinson's disease: An electrical neuroimaging study

In predictable contexts, motor inhibitory control can be deployed before the actual need for response suppression. The brain functional underpinnings of proactive inhibition, and notably the role of basal ganglia, are not entirely identified. We investigated the effects of deep brain stimulation of the subthalamic nucleus or internal globus pallidus on proactive inhibition in patients with Parkinson's disease. They completed a cued go/no-go proactive inhibition task ON and (unilateral) OFF stimulation while EEG was recorded. We found no behavioural effect of either subthalamic nucleus or internal globus pallidus deep brain stimulation on proactive inhibition, despite a general improvement of motor performance with subthalamic nucleus stimulation. In the non-operated and subthalamic nucleus group, we identified periods of topographic EEG modulation by the level of proactive inhibition. In the subthalamic nucleus group, source estimation analysis suggested the initial involvement of bilateral frontal and occipital areas, followed by a right lateralized fronto-basal network, and finally of right premotor and left parietal regions. Our results confirm the overall preservation of proactive inhibition capacities in both subthalamic nucleus and internal globus pallidus deep brain stimulation, and suggest a partly segregated network for proactive inhibition, with a preferential recruitment of the indirect pathway.

Mechanisms of Network Interactions for Flexible Cortico-Basal Ganglia-Mediated Action Control

In humans, finely tuned γ synchronization (60-90 Hz) rapidly appears at movement onset in a motor control network involving primary motor cortex, the basal ganglia and motor thalamus. Yet the functional consequences of brief movement-related synchronization are still unclear. Distinct synchronization phenomena have also been linked to different forms of motor inhibition, including relaxing antagonist muscles, rapid movement interruption and stabilizing network dynamics for sustained contractions. Here, I will introduce detailed hypotheses about how intrasite and intersite synchronization could interact with firing rate changes in different parts of the network to enable flexible action control. The here proposed cause-and-effect relationships shine a spotlight on potential key mechanisms of cortico-basal ganglia-thalamo-cortical (CBGTC) communication. Confirming or revising these hypotheses will be critical in understanding the neuronal basis of flexible movement initiation, invigoration and inhibition. Ultimately, the study of more complex cognitive phenomena will also become more tractable once we understand the neuronal mechanisms underlying behavioral readouts.

Normative vs. patient-specific brain connectivity in deep brain stimulation

Brain connectivity profiles seeding from deep brain stimulation (DBS) electrodes have emerged as informative tools to estimate outcome variability across DBS patients. Given the limitations of acquiring and processing patient-specific diffusion-weighted imaging data, a number of studies have employed normative atlases of the human connectome. To date, it remains unclear whether patient-specific connectivity information would strengthen the accuracy of such analyses. Here, we compared similarities and differences between patient-specific, disease-matched and normative structural connectivity data and their ability to predict clinical improvement. Data from 33 patients suffering from Parkinson's Disease who underwent surgery at three different centers were retrospectively collected. Stimulation-dependent connectivity profiles seeding from active contacts were estimated using three modalities, namely patient-specific diffusion-MRI data, age- and disease-matched or normative group connectome data (acquired in healthy young subjects). Based on these profiles, models of optimal connectivity were calculated and used to estimate clinical improvement in out of sample data. All three modalities resulted in highly similar optimal connectivity profiles that could largely reproduce findings from prior research based on this present novel multi-center cohort. In a data-driven approach that estimated optimal whole-brain connectivity profiles, out-of-sample predictions of clinical improvements were calculated. Using either patient-specific connectivity (R = 0.43 at p = 0.001), an age- and disease-matched group connectome (R = 0.25, p = 0.048) and a normative connectome based on healthy/young subjects (R = 0.31 at p = 0.028), significant predictions could be made. Our results of patient-specific connectivity and normative connectomes lead to similar main conclusions about which brain areas are associated with clinical improvement. Still, although results were not significantly different, they hint at the fact that patient-specific connectivity may bear the potential of explaining slightly more variance than group connectomes. Furthermore, use of normative connectomes involves datasets with high signal-to-noise acquired on specialized MRI hardware, while clinical datasets as the ones used here may not exactly match their quality. Our findings support the role of DBS electrode connectivity profiles as a promising method to investigate DBS effects and to potentially guide DBS programming.