Optimization and comparative evaluation of nonlinear deformation algorithms for atlas-based segmentation of DBS target nuclei

Premotor cortical beta synchronization and the network neuromodulation of externally paced finger tapping in Parkinson's disease

Parkinson's disease (PD) is characterized by the disruption of repetitive, concurrent and sequential motor actions due to compromised timing-functions principally located in cortex-basal ganglia (BG) circuits. Increasing evidence suggests that motor impairments in untreated PD patients are linked to an excessive synchronization of cortex-BG activity at beta frequencies (13-30 Hz). Levodopa and subthalamic nucleus deep brain stimulation (STN-DBS) suppress pathological beta-band reverberation and improve the motor symptoms in PD. Yet a dynamic tuning of beta oscillations in BG-cortical loops is fundamental for movement-timing and synchronization, and the impact of PD therapies on sensorimotor functions relying on neural transmission in the beta frequency-range remains controversial. Here, we set out to determine the differential effects of network neuromodulation through dopaminergic medication (ON and OFF levodopa) and STN-DBS (ON-DBS, OFF-DBS) on tapping synchronization and accompanying cortical activities. To this end, we conducted a rhythmic finger-tapping study with high-density EEG-recordings in 12 PD patients before and after surgery for STN-DBS and in 12 healthy controls. STN-DBS significantly ameliorated tapping parameters as frequency, amplitude and synchrony to the given auditory rhythms. Aberrant neurophysiologic signatures of sensorimotor feedback in the beta-range were found in PD patients: their neural modulation was weaker, temporally sluggish and less distributed over the right cortex in comparison to controls. Levodopa and STN-DBS boosted the dynamics of beta-band modulation over the right hemisphere, hinting to an improved timing of movements relying on tactile feedback. The strength of the post-event beta rebound over the supplementary motor area correlated significantly with the tapping asynchrony in patients, thus indexing the sensorimotor match between the external auditory pacing signals and the performed taps. PD patients showed an excessive interhemispheric coherence in the beta-frequency range during the finger-tapping task, while under DBS-ON the cortico-cortical connectivity in the beta-band was normalized. Ultimately, therapeutic DBS significantly ameliorated the auditory-motor coupling of PD patients, enhancing the electrophysiological processing of sensorimotor feedback-information related to beta-band activity, and thus allowing a more precise cued-tapping performance.

Deep brain stimulation of symptom-specific networks in Parkinson's disease

Deep Brain Stimulation can improve tremor, bradykinesia, rigidity, and axial symptoms in patients with Parkinson's disease. Potentially, improving each symptom may require stimulation of different white matter tracts. Here, we study a large cohort of patients (N = 237 from five centers) to identify tracts associated with improvements in each of the four symptom domains. Tremor improvements were associated with stimulation of tracts connected to primary motor cortex and cerebellum. In contrast, axial symptoms are associated with stimulation of tracts connected to the supplementary motor cortex and brainstem. Bradykinesia and rigidity improvements are associated with the stimulation of tracts connected to the supplementary motor and premotor cortices, respectively. We introduce an algorithm that uses these symptom-response tracts to suggest optimal stimulation parameters for DBS based on individual patient's symptom profiles. Application of the algorithm illustrates that our symptom-tract library may bear potential in personalizing stimulation treatment based on the symptoms that are most burdensome in an individual patient.

Probabilistic stimulation mapping from intra-operative thalamic deep brain stimulation data in essential tremor

Deep brain stimulation (DBS) is a therapy for Parkinson's disease (PD) and essential tremor (ET). The mechanism of action of DBS is still incompletely understood. Retrospective group analysis of intra-operative data recorded from ET patients implanted in the ventral intermediate nucleus of the thalamus (Vim) is rare. Intra-operative stimulation tests generate rich data and their use in group analysis has not yet been explored.Objective.To implement, evaluate, and apply a group analysis workflow to generate probabilistic stimulation maps (PSMs) using intra-operative stimulation data from ET patients implanted in Vim.Approach.A group-specific anatomical template was constructed based on the magnetic resonance imaging scans of 6 ET patients and 13 PD patients. Intra-operative test data (total:n= 1821) from the 6 ET patients was analyzed: patient-specific electric field simulations together with tremor assessments obtained by a wrist-based acceleration sensor were transferred to this template. Occurrence and weighted mean maps were generated. Voxels associated with symptomatic response were identified through a linear mixed model approach to form a PSM. Improvements predicted by the PSM were compared to those clinically assessed. Finally, the PSM clusters were compared to those obtained in a multicenter study using data from chronic stimulation effects in ET.Main results.Regions responsible for improvement identified on the PSM were in the posterior sub-thalamic area (PSA) and at the border between the Vim and ventro-oral nucleus of the thalamus (VO). The comparison with literature revealed a center-to-center distance of less than 5 mm and an overlap score (Dice) of 0.4 between the significant clusters. Our workflow and intra-operative test data from 6 ET-Vim patients identified effective stimulation areas in PSA and around Vim and VO, affirming existing medical literature.Significance.This study supports the potential of probabilistic analysis of intra-operative stimulation test data to reveal DBS's action mechanisms and to assist surgical planning.

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.

Whole brain pattern of iron accumulation in REM sleep behavior disorder

Isolated REM sleep behavior disorder (iRBD) is an early stage of synucleinopathy with most patients progressing to Parkinson's disease (PD) or related conditions. Quantitative susceptibility mapping (QSM) in PD has identified pathological iron accumulation in the substantia nigra (SN) and variably also in basal ganglia and cortex. Analyzing whole-brain QSM across iRBD, PD, and healthy controls (HC) may help to ascertain the extent of neurodegeneration in prodromal synucleinopathy. 70 de novo PD patients, 70 iRBD patients, and 60 HCs underwent 3 T MRI. T1 and susceptibility-weighted images were acquired and processed to space standardized QSM. Voxel-based analyses of grey matter magnetic susceptibility differences comparing all groups were performed on the whole brain and upper brainstem levels with the statistical threshold set at family-wise error-corrected p-values <.05. Whole-brain analysis showed increased susceptibility in the bilateral fronto-parietal cortex of iRBD patients compared to both PD and HC. This was not associated with cortical thinning according to the cortical thickness analysis. Compared to iRBD, PD patients had increased susceptibility in the left amygdala and hippocampal region. Upper brainstem analysis revealed increased susceptibility within the bilateral SN for both PD and iRBD compared to HC; changes were located predominantly in nigrosome 1 in the former and nigrosome 2 in the latter group. In the iRBD group, abnormal dopamine transporter SPECT was associated with increased susceptibility in nigrosome 1. iRBD patients display greater fronto-parietal cortex involvement than incidental early-stage PD cohort indicating more widespread subclinical neuropathology. Dopaminergic degeneration in the substantia nigra is paralleled by susceptibility increase, mainly in nigrosome 1.

Mapping dysfunctional circuits in the frontal cortex using deep brain stimulation

Frontal circuits play a critical role in motor, cognitive and affective processing, and their dysfunction may result in a variety of brain disorders. However, exactly which frontal domains mediate which (dys)functions remains largely elusive. We studied 534 deep brain stimulation electrodes implanted to treat four different brain disorders. By analyzing which connections were modulated for optimal therapeutic response across these disorders, we segregated the frontal cortex into circuits that had become dysfunctional in each of them. Dysfunctional circuits were topographically arranged from occipital to frontal, ranging from interconnections with sensorimotor cortices in dystonia, the primary motor cortex in Tourette's syndrome, the supplementary motor area in Parkinson's disease, to ventromedial prefrontal and anterior cingulate cortices in obsessive-compulsive disorder. Our findings highlight the integration of deep brain stimulation with brain connectomics as a powerful tool to explore couplings between brain structure and functional impairments in the human brain.

Subthalamic nucleus dynamics track microlesion effect in Parkinson's disease

Parkinson's Disease (PD) is characterized by the temporary alleviation of motor symptoms following electrode implantation (or nucleus destruction), known as the microlesion effect (MLE). Electrophysiological studies have explored different PD stages, but understanding electrophysiological characteristics during the MLE period remains unclear. The objective was to examine the characteristics of local field potential (LFP) signals in the subthalamic nucleus (STN) during the hyperacute period following implantation (within 2 days) and 1 month post-implantation. 15 patients diagnosed with PD were enrolled in this observational study, with seven simultaneous recordings of bilateral STN-LFP signals using wireless sensing technology from an implantable pulse generator. Recordings were made in both on and off medication states over 1 month after implantation. We used a method to parameterize the neuronal power spectrum to separate periodic oscillatory and aperiodic components effectively. Our results showed that beta power exhibited a significant increase in the off medication state 1 month after implantation, compared to the postoperative hyperacute period. Notably, this elevation was effectively attenuated by levodopa administration. Furthermore, both the exponents and offsets displayed a decrease at 1 month postoperatively when compared to the hyperacute postoperative period. Remarkably, levodopa medication exerted a modulatory effect on these aperiodic parameters, restoring them back to levels observed during the hyperacute period. Our findings suggest that both periodic and aperiodic components partially capture distinct electrophysiological characteristics during the MLE. It is crucial to adequately evaluate such discrepancies when exploring the mechanisms of MLE and optimizing adaptive stimulus protocols.

Identification of Parkinson's disease and multiple system atrophy using multimodal PET/MRI radiomics

OBJECTIVES

To construct a machine learning model for differentiating Parkinson's disease (PD) and multiple system atrophy (MSA) by using multimodal PET/MRI radiomics and clinical characteristics.

METHODS

One hundred and nineteen patients (81 with PD and 38 with MSA) underwent brain PET/CT and MRI to obtain metabolic images ([18F]FDG, [11C]CFT PET) and structural MRI (T1WI, T2WI, and T2-FLAIR). Image analysis included automatic segmentation on MRI, co-registration of PET images onto the corresponding MRI. Radiomics features were then extracted from the putamina and caudate nuclei and selected to construct predictive models. Moreover, based on PET/MRI radiomics and clinical characteristics, we developed a nomogram. Receiver operating characteristic (ROC) curves were performed to evaluate the performance of the models. Decision curve analysis (DCA) was employed to access the clinical usefulness of the models.

RESULTS

The combined PET/MRI radiomics model of five sequences outperformed monomodal radiomics models alone. Further, PET/MRI radiomics-clinical combined model could perfectly distinguish PD from MSA (AUC = 0.993), which outperformed the clinical model (AUC = 0.923, p = 0.028) in training set, with no significant difference in test set (AUC = 0.860 vs 0.917, p = 0.390). However, no significant difference was found between PET/MRI radiomics-clinical model and PET/MRI radiomics model in training (AUC = 0.988, p = 0.276) and test sets (AUC = 0.860 vs 0.845, p = 0.632). DCA demonstrated the highest clinical benefit of PET/MRI radiomics-clinical model.

CONCLUSIONS

Our study indicates that multimodal PET/MRI radiomics could achieve promising performance to differentiate between PD and MSA in clinics.

CLINICAL RELEVANCE STATEMENT

This study developed an optimal radiomics signature and construct model to distinguish PD from MSA by multimodal PET/MRI imaging methods in clinics for parkinsonian syndromes, which achieved an excellent performance.

KEY POINTS

•Multimodal PET/MRI radiomics from putamina and caudate nuclei increase the diagnostic efficiency for distinguishing PD from MSA. •The radiomics-based nomogram was developed to differentiate between PD and MSA. •Combining PET/MRI radiomics-clinical model achieved promising performance to identify PD and MSA.

WarpDrive: Improving spatial normalization using manual refinements

Spatial normalization-the process of mapping subject brain images to an average template brain-has evolved over the last 20+ years into a reliable method that facilitates the comparison of brain imaging results across patients, centers & modalities. While overall successful, sometimes, this automatic process yields suboptimal results, especially when dealing with brains with extensive neurodegeneration and atrophy patterns, or when high accuracy in specific regions is needed. Here we introduce WarpDrive, a novel tool for manual refinements of image alignment after automated registration. We show that the tool applied in a cohort of patients with Alzheimer's disease who underwent deep brain stimulation surgery helps create more accurate representations of the data as well as meaningful models to explain patient outcomes. The tool is built to handle any type of 3D imaging data, also allowing refinements in high-resolution imaging, including histology and multiple modalities to precisely aggregate multiple data sources together.

Deep Brain Stimulation for Obsessive-Compulsive Disorder: Optimal Stimulation Sites

BACKGROUND

Deep brain stimulation (DBS) is a promising treatment option for treatment-refractory obsessive-compulsive disorder (OCD). Several stimulation targets have been used, mostly in and around the anterior limb of the internal capsule and ventral striatum. However, the precise target within this region remains a matter of debate.

METHODS

Here, we retrospectively studied a multicenter cohort of 82 patients with OCD who underwent DBS of the ventral capsule/ventral striatum and mapped optimal stimulation sites in this region.

RESULTS

DBS sweet-spot mapping performed on a discovery set of 58 patients revealed 2 optimal stimulation sites associated with improvements on the Yale-Brown Obsessive Compulsive Scale, one in the anterior limb of the internal capsule that overlapped with a previously identified OCD-DBS response tract and one in the region of the inferior thalamic peduncle and bed nucleus of the stria terminalis. Critically, the nucleus accumbens proper and anterior commissure were associated with beneficial but suboptimal clinical improvements. Moreover, overlap with the resulting sweet- and sour-spots significantly estimated variance in outcomes in an independent cohort of 22 patients from 2 additional DBS centers. Finally, beyond obsessive-compulsive symptoms, stimulation of the anterior site was associated with optimal outcomes for both depression and anxiety, while the posterior site was only associated with improvements in depression.

CONCLUSIONS

Our results suggest how to refine targeting of DBS in OCD and may be helpful in guiding DBS programming in existing patients.

Combined Short-Pulse and Directional Deep Brain Stimulation of the Thalamic Ventral Intermediate Area for Essential Tremor

OBJECTIVE

Novel deep brain stimulation (DBS) systems allow directional and short-pulse stimulation to potentially improve symptoms and reduce side effects. The aim of this study was to investigate the effect of short-pulse and directional stimulation, in addition to a combination of both, in the ventral intermediate thalamus (VIM)/posterior subthalamic area (PSA) on tremor and stimulation-induced side effects in patients with essential tremor.

MATERIALS AND METHODS

We recruited 11 patients with essential tremor and VIM/PSA-DBS. Tremor severity (Fahn-Tolosa-Marin), ataxia (International Cooperative Ataxia Rating Scale), and paresthesia (visual analog scale) were assessed with conventional omnidirectional and directional stimulation with pulse width of 60 μs and 30 μs.

RESULTS

All stimulation conditions reduced tremor. The best directional stimulation with 60 μs reduced more tremor than did most other stimulation settings. The best directional stimulation, regardless of pulse width, effectively reduced stimulation-induced ataxia compared with the conventional stimulation (ring 60 μs) or worst directional stimulation with 60 μs. All new stimulation modes reduced occurrence of paresthesia, but only the best directional stimulation with 30 μs attenuated paresthesia compared with the conventional stimulation (ring 60 μs) or worst directional stimulation with 60 μs. The best directional stimulation with 30 μs reduced tremor, ataxia, and paresthesia compared with conventional stimulation in most patients. Correlation analyses indicated that more anterior stimulation sites are associated with stronger ataxia reduction with directional 30 μs than with conventional 60 μs stimulation.

CONCLUSION

Directional and short-pulse stimulation, and a combination of both, revealed beneficial effects on stimulation-induced adverse effects.

Local neuroanatomical and tract-based proxies of optimal subcallosal cingulate deep brain stimulation

BACKGROUND

Deep brain stimulation of the subcallosal cingulate area (SCC-DBS) is a promising neuromodulatory therapy for treatment-resistant depression (TRD). Biomarkers of optimal target engagement are needed to guide surgical targeting and stimulation parameter selection and to reduce variance in clinical outcome.

OBJECTIVE/HYPOTHESIS

We aimed to characterize the relationship between stimulation location, white matter tract engagement, and clinical outcome in a large (n = 60) TRD cohort treated with SCC-DBS. A smaller cohort (n = 22) of SCC-DBS patients with differing primary indications (bipolar disorder/anorexia nervosa) was utilized as an out-of-sample validation cohort.

METHODS

Volumes of tissue activated (VTAs) were constructed in standard space using high-resolution structural MRI and individual stimulation parameters. VTA-based probabilistic stimulation maps (PSMs) were generated to elucidate voxelwise spatial patterns of efficacious stimulation. A whole-brain tractogram derived from Human Connectome Project diffusion-weighted MRI data was seeded with VTA pairs, and white matter streamlines whose overlap with VTAs related to outcome ('discriminative' streamlines; Puncorrected < 0.05) were identified using t-tests. Linear modelling was used to interrogate the potential clinical relevance of VTA overlap with specific structures.

RESULTS

PSMs varied by hemisphere: high-value left-sided voxels were located more anterosuperiorly and squarely in the lateral white matter, while the equivalent right-sided voxels fell more posteroinferiorly and involved a greater proportion of grey matter. Positive discriminative streamlines localized to the bilateral (but primarily left) cingulum bundle, forceps minor/rostrum of corpus callosum, and bilateral uncinate fasciculus. Conversely, negative discriminative streamlines mostly belonged to the right cingulum bundle and bilateral uncinate fasciculus. The best performing linear model, which utilized information about VTA volume overlap with each of the positive discriminative streamline bundles as well as the negative discriminative elements of the right cingulum bundle, explained significant variance in clinical improvement in the primary TRD cohort (R = 0.46, P < 0.001) and survived repeated 10-fold cross-validation (R = 0.50, P = 0.040). This model was also able to predict outcome in the out-of-sample validation cohort (R = 0.43, P = 0.047).

CONCLUSION(S)

These findings reinforce prior indications of the importance of white matter engagement to SCC-DBS treatment success while providing new insights that could inform surgical targeting and stimulation parameter selection decisions.

Functional connectomic profile correlates with effective anterior thalamic stimulation for refractory epilepsy

BACKGROUND

Deep brain stimulation of the anterior nucleus of the thalamus (ANT-DBS) is an effective treatment for refractory epilepsy; however, seizure outcome varies among individuals. Identifying a reliable noninvasive biomarker to predict good responders would be helpful.

OBJECTIVES

To test whether the functional connectivity between the ANT-DBS sites and the seizure foci correlates with effective seizure control in refractory epilepsy.

METHODS

We performed a proof-of-concept pilot study of patients with focal refractory epilepsy receiving ANT-DBS. Using normative human connectome data derived from 1000 healthy participants, we investigated whether intrinsic functional connectivity between the seizure foci and the DBS site was associated with seizure outcome. We repeated this analysis controlling for the extent of seizure foci, distance between the seizure foci and DBS site, and using functional connectivity of the ANT instead of the DBS site to test the contribution of variance in DBS sites.

RESULTS

Eighteen patients with two or more seizure foci were included. Greater functional connectivity between the seizure foci and the DBS site correlated with more favorable outcome. The degree of functional connectivity accounted for significant variance in clinical outcomes (DBS site: |r| = 0.773, p < 0.001 vs ANT-atlas: |r| = 0.715, p = 0.001), which remained significant when controlling for the extent of the seizure foci (|r| = 0.773, p < 0.001) and the distance between the seizure foci and DBS site (|r| = 0.777, p < 0.001). Significant correlations were independent of variance in the DBS sites (|r| = 0.148, p = 0.57).

CONCLUSION

These findings suggest that functional connectomic profile is a potential reliable non-invasive biomarker to predict ANT-DBS outcomes. Accordingly, the identification of ANT responders could decrease the surgical risk for patients who may not benefit and optimize the cost-effective allocation of health care resources.

Mapping Dysfunctional Circuits in the Frontal Cortex Using Deep Brain Stimulation

Frontal circuits play a critical role in motor, cognitive, and affective processing - and their dysfunction may result in a variety of brain disorders. However, exactly which frontal domains mediate which (dys)function remains largely elusive. Here, we study 534 deep brain stimulation electrodes implanted to treat four different brain disorders. By analyzing which connections were modulated for optimal therapeutic response across these disorders, we segregate the frontal cortex into circuits that became dysfunctional in each of them. Dysfunctional circuits were topographically arranged from occipital to rostral, ranging from interconnections with sensorimotor cortices in dystonia, with the primary motor cortex in Tourette's syndrome, the supplementary motor area in Parkinson's disease, to ventromedial prefrontal and anterior cingulate cortices in obsessive-compulsive disorder. Our findings highlight the integration of deep brain stimulation with brain connectomics as a powerful tool to explore couplings between brain structure and functional impairment in the human brain.

Connectivity Profile for Subthalamic Nucleus Deep Brain Stimulation in Early Stage Parkinson Disease

OBJECTIVE

This study was undertaken to describe relationships between electrode localization and motor outcomes from the subthalamic nucleus (STN) deep brain stimulation (DBS) in early stage Parkinson disease (PD) pilot clinical trial.

METHODS

To determine anatomical and network correlates associated with motor outcomes for subjects randomized to early DBS (n = 14), voxelwise sweet spot mapping and structural connectivity analyses were carried out using outcomes of motor progression (Unified Parkinson Disease Rating Scale Part III [UPDRS-III] 7-day OFF scores [∆baseline➔24 months, MedOFF/StimOFF]) and symptomatic motor improvement (UPDRS-III ON scores [%∆baseline➔24 months, MedON/StimON]).

RESULTS

Sweet spot mapping revealed a location associated with slower motor progression in the dorsolateral STN (anterior/posterior commissure coordinates: 11.07 ± 0.82mm lateral, 1.83 ± 0.61mm posterior, 3.53 ± 0.38mm inferior to the midcommissural point; Montreal Neurological Institute coordinates: +11.25, -13.56, -7.44mm). Modulating fiber tracts from supplementary motor area (SMA) and primary motor cortex (M1) to the STN correlated with slower motor progression across STN DBS subjects, whereas fiber tracts originating from pre-SMA and cerebellum were negatively associated with motor progression. Robustness of the fiber tract model was demonstrated in leave-one-patient-out (R = 0.56, p = 0.02), 5-fold (R = 0.50, p = 0.03), and 10-fold (R = 0.53, p = 0.03) cross-validation paradigms. The sweet spot and fiber tracts associated with motor progression revealed strong similarities to symptomatic motor improvement sweet spot and connectivity in this early stage PD cohort.

INTERPRETATION

These results suggest that stimulating the dorsolateral region of the STN receiving input from M1 and SMA (but not pre-SMA) is associated with slower motor progression across subjects receiving STN DBS in early stage PD. This finding is hypothesis-generating and must be prospectively tested in a larger study. ANN NEUROL 2023;94:271-284.

Pupil size reflects activation of subcortical ascending arousal system nuclei during rest

Neuromodulatory nuclei that are part of the ascending arousal system (AAS) play a crucial role in regulating cortical state and optimizing task performance. Pupil diameter, under constant luminance conditions, is increasingly used as an index of activity of these AAS nuclei. Indeed, task-based functional imaging studies in humans have begun to provide evidence of stimulus-driven pupil-AAS coupling. However, whether there is such a tight pupil-AAS coupling during rest is not clear. To address this question, we examined simultaneously acquired resting-state fMRI and pupil-size data from 74 participants, focusing on six AAS nuclei: the locus coeruleus, ventral tegmental area, substantia nigra, dorsal and median raphe nuclei, and cholinergic basal forebrain. Activation in all six AAS nuclei was optimally correlated with pupil size at 0-2 s lags, suggesting that spontaneous pupil changes were almost immediately followed by corresponding BOLD-signal changes in the AAS. These results suggest that spontaneous changes in pupil size that occur during states of rest can be used as a noninvasive general index of activity in AAS nuclei. Importantly, the nature of pupil-AAS coupling during rest appears to be vastly different from the relatively slow canonical hemodynamic response function that has been used to characterize task-related pupil-AAS coupling.

Patient specific intracranial neural signatures of obsessions and compulsions in the ventral striatum

Objective. Deep brain stimulation is a treatment option for patients with refractory obsessive-compulsive disorder. A new generation of stimulators hold promise for closed loop stimulation, with adaptive stimulation in response to biologic signals. Here we aimed to discover a suitable biomarker in the ventral striatum in patients with obsessive compulsive disorder using local field potentials.Approach.We induced obsessions and compulsions in 11 patients undergoing deep brain stimulation treatment using a symptom provocation task. Then we trained machine learning models to predict symptoms using the recorded intracranial signal from the deep brain stimulation electrodes.Main results.Average areas under the receiver operating characteristics curve were 62.1% for obsessions and 78.2% for compulsions for patient specific models. For obsessions it reached over 85% in one patient, whereas performance was near chance level when the model was trained across patients. Optimal performances for obsessions and compulsions was obtained at different recording sites.Significance. The results from this study suggest that closed loop stimulation may be a viable option for obsessive-compulsive disorder, but that intracranial biomarkers are patient and not disorder specific.Clinical Trial:Netherlands trial registry NL7486.

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.

Diffusion Measures of Subcortical Structures Using High-Field MRI

The pathology of Parkinson’s disease (PD) involves the death of dopaminergic neurons in the substantia nigra (SN), which slowly influences downstream basal ganglia pathways as dopamine transport diminishes. Diffusion magnetic resonance imaging (MRI) has been used to diagnose PD by assessing white matter connectivity in some brain areas. For this study, we applied Lead-DBS to human connectome project data to automatically segment 11 subcortical structures of 49 human connectome project subjects, reducing the reliance on manual segmentation for more consistency. The Lead-connectome pipeline, which utilizes DSI Studio to generate structural connectomes from each 3T and 7T diffusion image, was applied to 3T and 7T data to investigate possible differences in diffusion measures due to different acquisition protocols. Significantly higher fractional anisotropy (FA) values were found in the 3T left SN; significantly higher MD values were found in the 3T left SN and the right amygdala, SN, and subthalamic nucleus (STN); significantly higher AD values were found in the right RN and STN; and significantly higher RD values were found in the left RN and right amygdala. We illustrate a methodology for obtaining diffusion measures of basal ganglia and basal ganglia connectivity using diffusion images, as well as show possible differences in diffusion measures that can arise due to the differences in MRI acquisitions.

Deep Brain Stimulation Electrode Reconstruction: Comparison between Lead-DBS and Surgical Planning System

BACKGROUND

Electrode reconstruction for postoperative deep brain simulation (DBS) can be achieved manually using a surgical planning system such as Surgiplan, or in a semi-automated manner using software such as the Lead-DBS toolbox. However, the accuracy of Lead-DBS has not been thoroughly addressed.

METHODS

In our study, we compared the DBS reconstruction results of Lead-DBS and Surgiplan. We included 26 patients (21 with Parkinson's disease and 5 with dystonia) who underwent subthalamic nucleus (STN)-DBS, and reconstructed the DBS electrodes using the Lead-DBS toolbox and Surgiplan. The electrode contact coordinates were compared between Lead-DBS and Surgiplan with postoperative CT and MRI. The relative positions of the electrode and STN were also compared between the methods. Finally, the optimal contact during follow-up was mapped onto the Lead-DBS reconstruction results to check for overlap between the contacts and the STN.

RESULTS

We found significant differences in all axes between Lead-DBS and Surgiplan with postoperative CT, with the mean variance for the X, Y, and Z coordinates being -0.13, -1.16, and 0.59 mm, respectively. Y and Z coordinates showed significant differences between Lead-DBS and Surgiplan with either postoperative CT or MRI. However, no significant difference in the relative distance of the electrode and the STN was found between the methods. All optimal contacts were located in the STN, with 70% of them located within the dorsolateral region of the STN in the Lead-DBS results.

CONCLUSIONS

Although significant differences in electrode coordinates existed between Lead-DBS and Surgiplan, our results suggest that the coordinate difference was around 1 mm, and Lead-DBS can capture the relative distance between the electrode and the DBS target, suggesting it is reasonably accurate for postoperative DBS reconstruction.

Evaluation of eight registration algorithms applied to the insula and insular gyri

BACKGROUND AND PURPOSE

Spatial registration is crucial in establishing correspondence between anatomic brain regions for research and clinical purposes. The insular cortex (IC) and gyri (IG) are implicated in various functions and pathologies including epilepsy. Optimizing registration of the insula to a common atlas can improve the accuracy of group-level analyses. Here, we compared six nonlinear, one linear, and one semiautomated registration algorithms (RAs) for registering the IC and IG to the Montreal Neurologic Institute standard space (MNI152).

METHODS

3T images acquired from 20 controls and 20 temporal lobe epilepsy patients with mesial temporal sclerosis underwent automated segmentation of the insula. This was followed by manual segmentation of the entire IC and six individual IGs. Consensus segmentations were created at 75% agreement for IC and IG before undergoing registration to MNI152 space with eight RAs. Dice similarity coefficients (DSCs) were calculated between segmentations after registration and the IC and IG in MNI152 space. Statistical analysis involved the Kruskal-Wallace test with Dunn's test for IC and two-way analysis of variance with Tukey's honest significant difference test for IG.

RESULTS

DSCs were significantly different between RAs. Based on multiple pairwise comparisons, we report that certain RAs performed better than others across population groups. Additionally, registration performance differed according to specific IG.

CONCLUSION

We compared different methods for registering the IC and IG to MNI152 space. We found differences in performance between RAs, which suggests that algorithm choice is important factor in analyses involving the insula.

Long-Term Recording of Subthalamic Aperiodic Activities and Beta Bursts in Parkinson's Disease

BACKGROUND

Local field potentials (LFPs) represent the summation of periodic (oscillations) and aperiodic (fractal) signals. Although previous studies showed changes in beta band oscillations and burst characteristics of the subthalamic nucleus (STN) in Parkinson's disease (PD), how aperiodic activity in the STN is related to PD pathophysiology is unknown.

OBJECTIVES

The study aimed to characterize the long-term effects of STN-deep brain stimulation (DBS) and dopaminergic medications on aperiodic activities and beta bursts.

METHODS

A total of 10 patients with PD participated in this longitudinal study. Simultaneous bilateral STN-LFP recordings were conducted in six separate visits during a period of 18 months using the Activa PC + S device in the off and on dopaminergic medication states. We used irregular-resampling auto-spectral analysis to separate oscillations and aperiodic components (exponent and offset) in the power spectrum of STN-LFP signals in beta band.

RESULTS

Our results revealed a systematic increase in both the exponent and the offset of the aperiodic spectrum over 18 months following the DBS implantation, independent of the dopaminergic medication state of patients with PD. In contrast, beta burst durations and amplitudes were stable over time and were suppressed by dopaminergic medications.

CONCLUSIONS

These findings indicate that oscillations and aperiodic activities reflect at least partially distinct yet complementary neural mechanisms, which should be considered in the design of robust biomarkers to optimize adaptive DBS. Given the link between increased gamma-aminobutyric acidergic (GABAergic) transmission and higher aperiodic activity, our findings suggest that long-term STN-DBS may relate to increased inhibition in the basal ganglia. © 2022 International Parkinson and Movement Disorder Society.

Decoupling of interacting neuronal populations by time-shifted stimulation through spike-timing-dependent plasticity

The synaptic organization of the brain is constantly modified by activity-dependent synaptic plasticity. In several neurological disorders, abnormal neuronal activity and pathological synaptic connectivity may significantly impair normal brain function. Reorganization of neuronal circuits by therapeutic stimulation has the potential to restore normal brain dynamics. Increasing evidence suggests that the temporal stimulation pattern crucially determines the long-lasting therapeutic effects of stimulation. Here, we tested whether a specific pattern of brain stimulation can enable the suppression of pathologically strong inter-population synaptic connectivity through spike-timing-dependent plasticity (STDP). More specifically, we tested how introducing a time shift between stimuli delivered to two interacting populations of neurons can effectively decouple them. To that end, we first used a tractable model, i.e., two bidirectionally coupled leaky integrate-and-fire (LIF) neurons, to theoretically analyze the optimal range of stimulation frequency and time shift for decoupling. We then extended our results to two reciprocally connected neuronal populations (modules) where inter-population delayed connections were modified by STDP. As predicted by the theoretical results, appropriately time-shifted stimulation causes a decoupling of the two-module system through STDP, i.e., by unlearning pathologically strong synaptic interactions between the two populations. Based on the overall topology of the connections, the decoupling of the two modules, in turn, causes a desynchronization of the populations that outlasts the cessation of stimulation. Decoupling effects of the time-shifted stimulation can be realized by time-shifted burst stimulation as well as time-shifted continuous simulation. Our results provide insight into the further optimization of a variety of multichannel stimulation protocols aiming at a therapeutic reshaping of diseased brain networks.

Globus pallidus internus deep brain stimulation evokes resonant neural activity in Parkinson's disease

Globus pallidus internus deep brain stimulation is an established therapy for patients with medication-refractory Parkinson's disease. Clinical outcomes are highly dependent on applying stimulation to precise locations in the brain. However, robust neurophysiological markers are needed to determine the optimal electrode location and to guide postoperative stimulation parameter selection. In this study, we evaluated evoked resonant neural activity in the pallidum as a potential intraoperative marker to optimize targeting and stimulation parameter selection to improve outcomes of deep brain stimulation for Parkinson's disease. Intraoperative local field potential recordings were acquired in 22 patients with Parkinson's disease undergoing globus pallidus internus deep brain stimulation implantation (N = 27 hemispheres). A control group of patients undergoing implantation in the subthalamic nucleus (N = 4 hemispheres) for Parkinson's disease or the thalamus for essential tremor (N = 9 patients) were included for comparison. High-frequency (135 Hz) stimulation was delivered from each electrode contact sequentially while recording the evoked response from the other contacts. Low-frequency stimulation (10 Hz) was also applied as a comparison. Evoked resonant neural activity features, including amplitude, frequency and localization were measured and analysed for correlation with empirically derived postoperative therapeutic stimulation parameters. Pallidal evoked resonant neural activity elicited by stimulation in the globus pallidus internus or externus was detected in 26 of 27 hemispheres and varied across hemispheres and across stimulating contacts within individual hemispheres. Bursts of high-frequency stimulation elicited evoked resonant neural activity with similar amplitudes (P = 0.9) but a higher frequency (P = 0.009) and a higher number of peaks (P = 0.004) than low-frequency stimulation. We identified a 'hotspot' in the postero-dorsal pallidum where stimulation elicited higher evoked resonant neural activity amplitudes (P < 0.001). In 69.6% of hemispheres, the contact that elicited the maximum amplitude intraoperatively matched the contact empirically selected for chronic therapeutic stimulation by an expert clinician after 4 months of programming sessions. Pallidal and subthalamic nucleus evoked resonant neural activity were similar except for lower pallidal amplitudes. No evoked resonant neural activity was detected in the essential tremor control group. Given its spatial topography and correlation with postoperative stimulation parameters empirically selected by expert clinicians, pallidal evoked resonant neural activity shows promise as a potential marker to guide intraoperative targeting and to assist the clinician with postoperative stimulation programming. Importantly, evoked resonant neural activity may also have the potential to guide directional and closed-loop deep brain stimulation programming for Parkinson's disease.

Automatic localization of target point for subthalamic nucleus-deep brain stimulation via hierarchical attention-UNet based MRI segmentation

BACKGROUND

Deep brain stimulation of the subthalamic nucleus (STN-DBS) is an effective treatment for patients with advanced Parkinson's disease, the outcome of this surgery is highly dependent on the accurate placement of the electrode in the optimal target of STN.

PURPOSE

In this study, we aim to develop a target localization pipeline for DBS surgery, considering that the heart of this matter is to achieve the STN and red nucleus segmentation, a deep learning-based automatic segmentation approach is proposed to tackle this issue.

METHODS

To address the problems of ambiguous boundaries and variable shape of the segmentation targets, the hierarchical attention mechanism with two different attention strategies is integrated into an encoder-decoder network for mining both semantics and fine-grained details for segmentation. The hierarchical attention mechanism is utilized to suppress irrelevant regions in magnetic resonance (MR) images while build long-range dependency among segmentation targets. Specifically, the attention gate (AG) is integrated into low-level features to suppress irrelevant regions in an input image while highlighting the salient features useful for segmentation. Besides, the self-attention involved in the transformer block is integrated into high-level features to model the global context. Ninety-nine brain magnetic resonance imaging (MRI) studies were collected from 99 patients with Parkinson's disease undergoing STN-DBS surgery, among which 80 samples were randomly selected as the training datasets for deep learning training, and ground truths (segmentation masks) were manually generated by radiologists.

RESULTS

We applied five-fold cross-validation on these data to train our model, the mean results on 19 test samples are used to conduct the comparison experiments, the Dice similarity coefficient (DSC), Jaccard (JA), sensitivity (SEN), and HD95 of the segmentation for STN are 88.20%, 80.32%, 90.13%, and 1.14 mm, respectively, outperforming the state-of-the-art STN segmentation method with 2.82%, 4.52%, 2.56%, and 0.02 mm respectively. The source code and trained models of this work have been released in the URL below: https://github.com/liuruiqiang/HAUNet/tree/master.

CONCLUSIONS

In this study, we demonstrate the effectiveness of the hierarchical attention mechanism for building global dependency on high-level semantic features and enhancing the fine-grained details on low-level features, the experimental results show that our method has considerable superiority for STN and red nucleus segmentation, which can provide accurate target localization for STN-DBS.

Lead location as a determinant of motor benefit in subthalamic nucleus deep brain stimulation for Parkinson’s disease

Background

Subthalamic nucleus (STN) deep brain stimulation (DBS) is regarded as an effective treatment for patients with advanced Parkinson’s disease (PD). Clinical benefit, however, varies significantly across patients. Lead location has been hypothesized to play a critical role in determining motor outcome and may account for much of the observed variability reported among patients.

Objective

To retrospectively evaluate the relationship of lead location to motor outcomes in patients who had been implanted previously at another center by employing a novel visualization technology that more precisely determines the location of the DBS lead and its contacts with respect to each patient’s individually defined STN.

Methods

Anatomical models were generated using novel imaging in 40 PD patients who had undergone bilateral STN DBS (80 electrodes) at another center. Patient-specific models of each STN were evaluated to determine DBS electrode contact locations with respect to anterior to posterior and medial to lateral regions of the individualized STNs and compared to the change in the contralateral hemi-body Unified Parkinson’s Disease Rating Scale Part III (UPDRS-III) motor score.

Results

The greatest improvement in hemi-body motor function was found when active contacts were located within the posterolateral portion of the STN (71.5%). Motor benefit was 52 and 36% for central and anterior segments, respectively. Active contacts within the posterolateral portion also demonstrated the greatest reduction in levodopa dosage (77%).

Conclusion

The degree of motor benefit was dependent on the location of the stimulating contact within the STN. Although other factors may play a role, we provide further evidence in support of the hypothesis that lead location is a critical factor in determining clinical outcomes in STN DBS.

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.

Joint Progressive and Coarse-to-Fine Registration of Brain MRI via Deformation Field Integration and Non-Rigid Feature Fusion

Registration of brain MRI images requires to solve a deformation field, which is extremely difficult in aligning intricate brain tissues, e.g., subcortical nuclei, etc. Existing efforts resort to decomposing the target deformation field into intermediate sub-fields with either tiny motions, i.e., progressive registration stage by stage, or lower resolutions, i.e., coarse-to-fine estimation of the full-size deformation field. In this paper, we argue that those efforts are not mutually exclusive, and propose a unified framework for robust brain MRI registration in both progressive and coarse-to-fine manners simultaneously. Specifically, building on a dual-encoder U-Net, the fixed-moving MRI pair is encoded and decoded into multi-scale sub-fields from coarse to fine. Each decoding block contains two proposed novel modules: i) in Deformation Field Integration (DFI), a single integrated deformation sub-field is calculated, warping by which is equivalent to warping progressively by sub-fields from all previous decoding blocks, and ii) in Non-rigid Feature Fusion (NFF), features of the fixed-moving pair are aligned by DFI-integrated deformation field, and then fused to predict a finer sub-field. Leveraging both DFI and NFF, the target deformation field is factorized into multi-scale sub-fields, where the coarser fields alleviate the estimate of a finer one and the finer field learns to make up those misalignments insolvable by previous coarser ones. The extensive and comprehensive experimental results on both private and two public datasets demonstrate a superior registration performance of brain MRI images over progressive registration only and coarse-to-fine estimation only, with an increase by at most 8% in the average Dice.

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.

Probabilistic maps for deep brain stimulation - Impact of methodological differences

BACKGROUND

Group analysis of patients with deep brain stimulation (DBS) has the potential to help understand and optimize the treatment of patients with movement disorders. Probabilistic stimulation maps (PSM) are commonly used to analyze the correlation between tissue stimulation and symptomatic effect but are applied with different methodological variations.

OBJECTIVE

To compute a group-specific MRI template and PSMs for investigating the impact of PSM model parameters.

METHODS

Improvement and occurrence of dizziness in 68 essential tremor patients implanted in caudal zona incerta were analyzed. The input data includes the best parameters for each electrode contact (screening), and the clinically used settings. Patient-specific electric field simulations (n = 488) were computed for all DBS settings. The electric fields were transformed to a group-specific MRI template for analysis and visualization. The different comparisons were based on PSMs representing occurrence (N-map), mean improvement (M-map), weighted mean improvement (wM-map), and voxel-wise t-statistics (p-map). These maps were used to investigate the impact from input data (clinical/screening settings), clustering methods, sampling resolution, and weighting function.

RESULTS

Screening or clinical settings showed the largest impacts on the PSMs. The average differences of wM-maps were 12.4 and 18.2% points for the left and right sides respectively. Extracting clusters based on wM-map or p-map showed notable variation in volumes, while positioning was similar. The impact on the PSMs was small from weighting functions, except for a clear shift in the positioning of the wM-map clusters.

CONCLUSION

The distribution of the input data and the clustering method are most important to consider when creating PSMs for studying the relationship between anatomy and DBS outcome.

Interrater reliability of deep brain stimulation electrode localizations

Lead-DBS is an open-source, semi-automatized and widely applied software tool facilitating precise localization of deep brain stimulation electrodes both in native as well as in standardized stereotactic space. While automatized preprocessing steps within the toolbox have been tested and validated in previous studies, the interrater reliability in manual refinements of electrode localizations using the tool has not been objectified so far. Here, we investigate the variance introduced in this processing step by different raters when localizing electrodes based on postoperative CT or MRI. Furthermore, we compare the performance of novel trainees that received a structured training and more experienced raters with an expert user. We show that all users yield similar results with an average difference in localizations ranging between 0.52-0.75 mm with 0.07-0.12 mm increases in variability when using postoperative MRI and following normalization to standard space. Our findings may pave the way toward formal training for using Lead-DBS and demonstrate its reliability and ease-of-use for imaging research in the field of deep brain stimulation.

Lead-OR: a multimodal platform for deep brain stimulation surgery

Background:

Deep brain stimulation (DBS) electrode implant trajectories are stereotactically defined using preoperative neuroimaging. To validate the correct trajectory, microelectrode recordings (MERs) or local field potential recordings can be used to extend neuroanatomical information (defined by MRI) with neurophysiological activity patterns recorded from micro- and macroelectrodes probing the surgical target site. Currently, these two sources of information (imaging vs. electrophysiology) are analyzed separately, while means to fuse both data streams have not been introduced.

Methods:

Here, we present a tool that integrates resources from stereotactic planning, neuroimaging, MER, and high-resolution atlas data to create a real-time visualization of the implant trajectory. We validate the tool based on a retrospective cohort of DBS patients (N = 52) offline and present single-use cases of the real-time platform.

Results:

We establish an open-source software tool for multimodal data visualization and analysis during DBS surgery. We show a general correspondence between features derived from neuroimaging and electrophysiological recordings and present examples that demonstrate the functionality of the tool.

Conclusions:

This novel software platform for multimodal data visualization and analysis bears translational potential to improve accuracy of DBS surgery. The toolbox is made openly available and is extendable to integrate with additional software packages.

Funding:

Deutsche Forschungsgesellschaft (410169619, 424778381), Deutsches Zentrum für Luft- und Raumfahrt (DynaSti), National Institutes of Health (2R01 MH113929), and Foundation for OCD Research (FFOR).

Deep brain stimulation is an established therapy for patients with Parkinson’s disease and an emerging option for other neurological conditions. Electrodes are implanted deep in the brain to stimulate precise brain regions and control abnormal brain activity in those areas. The most common target for Parkinson’s disease, for instance, is a structure called the subthalamic nucleus, which sits at the base of the brain, just above the brain stem.

To ensure electrodes are placed correctly, surgeons use various sources of information to characterize the patient’s brain anatomy and decide on an implant site. These data include brain scans taken before surgery and recordings of brain activity taken during surgery to confirm the intended implant site. Sometimes, the brain activity signals from this last confirmation step may slightly alter surgical plans. It represents one of many challenges for clinical teams: to analyse, assimilate, and communicate data as it is collected during the procedure.

Oxenford et al. developed a software pipeline to aggregate the data surgeons use to implant electrodes. The open-source platform, dubbed Lead-OR, visualises imaging data and brain activity recordings (termed electrophysiology data) in real time. The current set-up integrates with commercial tools and existing software for surgical planning.

Oxenford et al. tested Lead-OR on data gathered retrospectively from 32 patients with Parkinson’s who had electrodes implanted in their subthalamic nucleus. The platform showed good agreement between imaging and electrophysiology data, although there were some unavoidable discrepancies, arising from limitations in the imaging pipeline and from the surgical procedure. Lead-OR was also able to correct for brain shift, which is where the brain moves ever so slightly in the skull.

With further validation, this proof-of-concept software could serve as a useful decision-making tool for surgical teams implanting electrodes for deep brain stimulation. In time, if implemented, its use could improve the accuracy of electrode placement, translating into better surgical outcomes for patients. It also has the potential to integrate forthcoming ultra-high-resolution data from current brain mapping projects, and other commercial surgical planning tools.

Functional connectivity maps of theta/alpha and beta coherence within the subthalamic nucleus region

The subthalamic nucleus (STN) is a primary target for deep brain stimulation in Parkinson's disease (PD). Although small in size, the STN is commonly partitioned into sensorimotor, cognitive/associative, and limbic subregions based on its structural connectivity profile to cortical areas. We investigated whether such a regional specialization is also supported by functional connectivity between local field potential recordings and simultaneous magnetoencephalography. Using a novel data set of 21 PD patients, we replicated previously reported cortico-STN coherence networks in the theta/alpha and beta frequency ranges, and looked for the spatial distribution of these networks within the STN region. Although theta/alpha and beta coherence peaks were both observed in on-medication recordings from electrode contacts at several locations within and around the STN, sites with theta/alpha coherence peaks were situated at significantly more inferior MNI coordinates than beta coherence peaks. Sites with only theta/alpha coherence peaks, i.e. without distinct beta coherence, were mostly located near the border of sensorimotor and cognitive/associative subregions as defined by a tractography-based atlas of the STN. Peak coherence values were largely unaltered by the medication state of the subject, however, theta/alpha peaks were more often identified in recordings obtained after administration of dopaminergic medication. Our findings suggest the existence of a frequency-specific topography of cortico-STN coherence within the STN, albeit with considerable spatial overlap between functional networks. Consequently, optimization of deep brain stimulation targeting might remain a trade-off between alleviating motor symptoms and avoiding adverse neuropsychiatric side effects.

Optimal deep brain stimulation sites and networks for cervical vs. generalized dystonia

We studied deep brain stimulation effects in two types of dystonia and conclude that different specific connections between the pallidum and thalamus are responsible for optimal treatment effects. Since alternative treatment options for dystonia beyond deep brain stimulation are scarce, our results will be crucial to maximize treatment outcome in this population of patients.

Dystonia is a debilitating disease with few treatment options. One effective option is deep brain stimulation (DBS) to the internal pallidum. While cervical and generalized forms of isolated dystonia have been targeted with a common approach to the posterior third of the nucleus, large-scale investigations regarding optimal stimulation sites and potential network effects have not been carried out. Here, we retrospectively studied clinical results following DBS for cervical and generalized dystonia in a multicenter cohort of 80 patients. We model DBS electrode placement based on pre- and postoperative imaging and introduce an approach to map optimal stimulation sites to anatomical space. Second, we investigate which tracts account for optimal clinical improvements, when modulated. Third, we investigate distributed stimulation effects on a whole-brain functional connectome level. Our results show marked differences of optimal stimulation sites that map to the somatotopic structure of the internal pallidum. While modulation of the striatopallidofugal axis of the basal ganglia accounted for optimal treatment of cervical dystonia, modulation of pallidothalamic bundles did so in generalized dystonia. Finally, we show a common multisynaptic network substrate for both phenotypes in the form of connectivity to the cerebellum and somatomotor cortex. Our results suggest a brief divergence of optimal stimulation networks for cervical vs. generalized dystonia within the pallidothalamic loop that merge again on a thalamo-cortical level and share a common whole-brain network.

Brain Structures and Networks Underlying Treatment Response to Deep Brain Stimulation Targeting the Inferior Thalamic Peduncle in Obsessive-Compulsive Disorder

<b><i>Background:</i></b> Obsessive-compulsive disorder (OCD) is a debilitating disease with a lifetime prevalence of 2–3%. Neuromodulatory treatments have been successfully used in severe cases. Deep brain stimulation (DBS) targeting the inferior thalamic peduncle (ITP) has been shown to successfully alleviate symptoms in OCD patients; however, the brain circuits implicated remain unclear. Here, we investigate the efficacious neural substrates following ITP-DBS for OCD. <b><i>Methods:</i></b> High-quality normative structural and functional connectomics and voxel-wise probabilistic mapping techniques were applied to assess the neural substrates of OCD symptom alleviation in a cohort of 5 ITP-DBS patients. <b><i>Results:</i></b> The region of most efficacious stimulation was located in the regions of the ITP and bed nucleus of the stria terminalis. Both functional and structural connectomics analyses demonstrated that successful symptom alleviation involved a brain network encompassing the bilateral amygdala and prefrontal regions. <b><i>Limitations:</i></b> The main limitation is the small size of the ITP-DBS cohort. While the findings are highly consistent and significant, these should be validated in larger studies. <b><i>Conclusions:</i></b> These results identify a tripartite brain network – composed of the bilateral amygdala and prefrontal regions 24 and 46 – whose engagement is associated with greater symptom improvement. They also provide information for optimizing targeting and identifying network components critically involved in ITP-DBS treatment response. Amygdala engagement in particular seems to be a key component for clinical benefits and could constitute a biomarker for treatment optimization.

Quantifying Differences Between Affine and Nonlinear Spatial Normalization of FP-CIT Spect Images

Spatial normalization helps us to compare quantitatively two or more input brain scans. Although using an affine normalization approach preserves the anatomical structures, the neuroimaging field is more common to find works that make use of nonlinear transformations. The main reason is that they facilitate a voxel-wise comparison, not only when studying functional images but also when comparing MRI scans given that they fit better to a reference template. However, the amount of bias introduced by the nonlinear transformations can potentially alter the final outcome of a diagnosis especially when studying functional scans for neurological disorders like Parkinson's Disease. In this context, we have tried to quantify the bias introduced by the affine and the nonlinear spatial registration of FP-CIT SPECT volumes of healthy control subjects and patients with PD. For that purpose, we calculated the deformation fields of each participant and applied these deformation fields to a 3D-grid. As the space between the edges of small cubes comprising the grid change, we can quantify which parts from the brain have been enlarged, compressed or just remain the same. When the nonlinear approach is applied, scans from PD patients show a region near their striatum very similar in shape to that of healthy subjects. This artificially increases the interclass separation between patients with PD and healthy subjects as the local intensity is decreased in the latter region, and leads machine learning systems to biased results due to the artificial information introduced by these deformations.

Past, Present, and Future of Deep Brain Stimulation: Hardware, Software, Imaging, Physiology and Novel Approaches

Deep brain stimulation (DBS) has advanced treatment options for a variety of neurologic and neuropsychiatric conditions. As the technology for DBS continues to progress, treatment efficacy will continue to improve and disease indications will expand. Hardware advances such as longer-lasting batteries will reduce the frequency of battery replacement and segmented leads will facilitate improvements in the effectiveness of stimulation and have the potential to minimize stimulation side effects. Targeting advances such as specialized imaging sequences and “connectomics” will facilitate improved accuracy for lead positioning and trajectory planning. Software advances such as closed-loop stimulation and remote programming will enable DBS to be a more personalized and accessible technology. The future of DBS continues to be promising and holds the potential to further improve quality of life. In this review we will address the past, present and future of DBS.

The Contribution of Subthalamic Nucleus Deep Brain Stimulation to the Improvement in Motor Functions and Quality of Life

BACKGROUND

Subthalamic nucleus deep brain stimulation (STN-DBS) effectively treats motor symptoms and quality of life (QoL) of advanced and fluctuating early Parkinson's disease. Little is known about the relation between electrode position and changes in symptom control and ultimately QoL.

OBJECTIVES

The relation between the stimulated part of the STN and clinical outcomes, including the motor score of the Unified Parkinson's Disease Rating Scale (UPDRS) and the quality-of-life questionnaire, was assessed in a subcohort of the EARLYSTIM study.

METHODS

Sixty-nine patients from the EARLYSTIM cohort who underwent DBS, with a comprehensive clinical characterization before and 24 months after surgery, were included. Intercorrelations of clinical outcome changes, correlation between the affected functional parts of the STN, and changes in clinical outcomes were investigated. We further calculated sweet spots for different clinical parameters.

RESULTS

Improvements in the UPDRS III and Parkinson's Disease Questionnaire (PDQ-39) correlated positively with the extent of the overlap with the sensorimotor STN. The sweet spots for the UPDRS III (x = 11.6, y = -13.1, z = -6.3) and the PDQ-39 differed (x = 14.8, y = -12.4, z = -4.3) ~3.8 mm.

CONCLUSIONS

The main influence of DBS on QoL is likely mediated through the sensory-motor basal ganglia loop. The PDQ sweet spot is located in a posteroventral spatial location in the STN territory. For aspects of QoL, however, there was also evidence of improvement through stimulation of the other STN subnuclei. More research is necessary to customize the DBS target to individual symptoms of each patient. © 2022 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

White Matter Connectivity between Structures of the Basal Ganglia using 3T and 7T

Analysis of the basal ganglia has been important in investigating the effects of Parkinson's disease as well as treatments for Parkinson's disease. One method of analysis has been using MRI for non-invasively segmenting the basal ganglia, then investigating significant parameters that involve the basal ganglia, such as fiber orientations and positional markers for deep brain stimulation (DBS). Following enhancements to optimizations and improvements to 3T and 7T MRI acquisitions, we utilized Lead-DBS on human connectome project data to automatically segment the basal ganglia of 49 human connectome project subjects, reducing the reliance on manual segmentation for more consistency. We generated probabilistic tractography streamlines between each segmentation pair using 3T and 7T human connectome diffusion data to observe any major differences in tractography streamline patterns that can arise due to tradeoffs from different field strengths and acquisitions. Tractography streamlines generated between basal ganglia structures using 3T images showed less standard deviation in streamline count than using 7T images. Mean tractography streamline counts generated using 3T diffusion images were all higher in count than streamlines generated using 7T diffusion images. We illustrate a potential method for analyzing the structural connectivity between basal ganglia structures, as well as visualize possible differences in probabilistic tractography that can arise from different acquisition protocols.

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.

Diffusion Tensor Imaging Changes Do Not Affect Long-Term Neurodevelopment following Early Erythropoietin among Extremely Preterm Infants in the Preterm Erythropoietin Neuroprotection Trial

We aimed to evaluate diffusion tensor imaging (DTI) in infants born extremely preterm, to determine the effect of erythropoietin (Epo) on DTI, and to correlate DTI with neurodevelopmental outcomes at 2 years of age for infants in the Preterm Erythropoietin Neuroprotection (PENUT) Trial. Infants who underwent MRI with DTI at 36 weeks postmenstrual age were included. Neurodevelopmental outcomes were evaluated by Bayley Scales of Infant and Toddler Development (BSID-III). Generalized linear models were used to assess the association between DTI parameters and treatment group, and then with neurodevelopmental outcomes. A total of 101 placebo- and 93 Epo-treated infants underwent MRI. DTI white matter mean diffusivity (MD) was lower in placebo- compared to Epo-treated infants in the cingulate and occipital regions, and occipital white matter fractional isotropy (FA) was lower in infants born at 24-25 weeks vs. 26-27 weeks. These values were not associated with lower BSID-III scores. Certain decreases in clustering coefficients tended to have lower BSID-III scores. Consistent with the PENUT Trial findings, there was no effect on long-term neurodevelopment in Epo-treated infants even in the presence of microstructural changes identified by DTI.

Focused Ultrasound Thalamotomy Sensory Side Effects Follow the Thalamic Structural Homunculus

Objective

Focused ultrasound thalamotomy is an effective treatment for tremor; however, side effects may occur. The purpose of the present study was to investigate the spatial relationship between thalamotomies and specific sensory side effects and their functional connectivity with somatosensory cortex and relationship to the medial lemniscus (ML).

Methods

Sensory adverse effects were categorized into 4 groups based on the location of the disturbance: face/mouth/tongue numbness/paresthesia, hand-only paresthesia, hemibody/limb paresthesia, and dysgeusia. Then, areas of significant risk (ASRs) for each category were defined using voxel-wise mass univariate analysis and overlaid on corresponding odds ratio maps. The ASR associated with the maximum risk was used as a region of interest in a normative functional connectome to determine side effect-specific functional connectivity. Finally, each ASR was overlaid on the ML derived from normative template.

Results

Of 103 patients, 17 developed sensory side effects after thalamotomy persisting 3 months after the procedures. Lesions producing sensory side effects extended posteriorly into the principle sensory nucleus of the thalamus or below the thalamus in the ML. The topography of sensory adverse effects followed the known somatotopy of the ML and the sensory nucleus. Functional connectivity patterns between each sensory-specific thalamic seed and the primary somatosensory areas supported the role of the middle insula in processing of gustatory information and in multisensory integration.

Conclusions

Distinct regions in the sensory thalamus and its afferent connections rise to specific sensory disturbances. These findings demonstrate the relationship between the sensory thalamus, ML, and bilateral sensory cortical areas.

HybraPD atlas: Towards precise subcortical nuclei segmentation using multimodality medical images in patients with Parkinson disease

Human brain atlases are essential for research and surgical treatment of Parkinson's disease (PD). For example, deep brain stimulation for PD often requires human brain atlases for brain structure identification. However, few atlases can provide disease-specific subcortical structures for PD, and most of them are based on T1w and T2w images. In this work, we construct a HybraPD atlas using fused quantitative susceptibility mapping (QSM) and T1w images from 87 patients with PD. The constructed HybraPD atlas provides a series of templates, that is, T1w, GRE magnitude, QSM, R2*, and brain tissue probabilistic maps. Then, we manually delineate a parcellation map with 12 bilateral subcortical nuclei, which are highly related to PD pathology, such as sub-regions in globus pallidus and substantia nigra. Furthermore, we build a whole-brain parcellation map by combining existing cortical parcellation and white-matter segmentation with the proposed subcortical nuclei map. Considering the multimodality of the HybraPD atlas, the segmentation accuracy of each nucleus is evaluated using T1w and QSM templates, respectively. The results show that the HybraPD atlas provides more accurate segmentation than existing atlases. Moreover, we analyze the metabolic difference in subcortical nuclei between PD patients and healthy control subjects by applying the HybraPD atlas to calculate uptake values of contrast agents on positron emission tomography (PET) images. The atlas-based analysis generates accurate disease-related brain nuclei segmentation on PET images. The newly developed HybraPD atlas could serve as an efficient template to study brain pathological alterations in subcortical regions for PD research.

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.

Flexible vs. standard subthalamic stimulation in Parkinson disease: A double-blind proof-of-concept cross-over trial

BACKGROUND

Deep brain stimulation (DBS) of the subthalamus (STN) is effective for the treatment of cardinal motor signs of Parkinson disease (PD). Structures around the STN can suppress dyskinesia and tremor (zona incerta) and improve gait and balance (substantia nigra pars reticulata).

OBJECTIVE

Is the newer 8-contact linear lead connected to a 'flexible' DBS system superior to standard 4-contact stimulation in PD patients receiving STN DBS?

METHODS

After 3 months of open label programming, 10 patients were randomized to standard or flexible stimulation before crossing over to the other arm (3 months each period). Patients and assessors were blinded.

RESULTS

A trend to improvement in Patient Global Impression of Change scores was seen with standard to flexible stimulation and worsening from flexible to standard stimulation (mean ± SD: 0.7 ± 1.2 and -0.4 ± 1.5 respectively, p = 0.152). There was a significant reduction in the number of troublesome symptoms reported prior to DBS (2.6 ± 3.3 per patient), more so with flexible stimulation (0.4 ± 0.6 vs. 1.5 ± 1.6 with standard stimulation, p = 0.001 and p = 0.034). There was no significant difference between the flexible and standard stimulation groups.

CONCLUSION

Further studies confirming that flexible stimulation is superior to standard DBS are warranted.

Comparison between patient-specific deep brain stimulation simulations and commercial system SureTune3

Objective. Software to visualize estimated volume of tissue activated (VTA) in deep brain stimulation assuming a homogeneous tissue surrounding such as SureTune3 has recently become available for clinical use. The objective of this study is to compare SureTune3 with homogeneous and heterogeneous patient-specific finite element method (FEM) simulations of the VTA to elucidate how well they coincide in their estimates.Approach. FEM simulations of the VTA were performed in COMSOL Multiphysics and compared with VTA from SureTune3 with variation of voltage and current amplitude, pulse width, axon diameter, number of active contacts, and surrounding homogeneous grey or white matter. Patient-specific simulations with heterogeneous tissue were also performed.Main results. The VTAs corresponded well for voltage control in homogeneous tissue, though with the smallest VTAs being slightly larger in SureTune3 and the largest VTAs being slightly larger in the FEM simulations. In current control, FEM estimated larger VTAs in white matter and smaller VTAs in grey matter compared to SureTune3 as grey matter has higher electric conductivity than white matter and requires less voltage to reach the same current. The VTAs also corresponded well in the patient-specific cases except for one case with a cyst of highly conductive cerebrospinal fluid (CSF) near the active contacts.Significance. The VTA estimates without taking the surrounding tissue into account in SureTune3 are in good agreement with patient-specific FEM simulations when using voltage control in the absence of CSF-filled cyst. In current control or when CSF is present near the active contacts, the tissue characteristics are important for the VTA and needs consideration.Clinical. trial ethical approval: Local ethics committee at Linköping University (2012/434-31).

Fields of Forel Brain Stimulation Improves Levodopa-Unresponsive Gait and Balance Disorders in Parkinson's Disease

BACKGROUND

Gait and balance disturbance are challenging symptoms in advanced Parkinson's disease (PD). Anatomic and clinical data suggest that the fields of Forel may be a potential surgical target to treat these symptoms.

OBJECTIVE

To test whether bilateral stimulation centered at the fields of Forel improves levodopa unresponsive freezing of gait (FOG), balance problems, postural instability, and falls in PD.

METHODS

A total of 13 patients with levodopa-unresponsive gait disturbance (Hoehn and Yahr stage ≥3) were included. Patients were evaluated before (on-medication condition) and 1 yr after surgery (on-medication-on-stimulation condition). Motor symptoms and quality of life were assessed with the Unified Parkinson's Disease Rating scale (UPDRS III) and Quality of Life scale (PDQ-39). Clinical and instrumented analyses assessed gait, balance, postural instability, and falls.

RESULTS

Surgery improved balance by 43% (95% confidence interval [CI]: 21.2-36.4 to 35.2-47.1; P = .0012), reduced FOG by 35% (95% CI: 15.1-20.3 to 8.1-15.3; P = .0021), and the monthly number of falls by 82.2% (95% CI: 2.2-6.9 to -0.2-1.7; P = .0039). Anticipatory postural adjustments, velocity to turn, and postural sway measurements also improved 1 yr after deep brain stimulation (DBS). UPDRS III motor scores were reduced by 27.2% postoperatively (95% CI: 42.6-54.3 to 30.2-40.5; P < .0001). Quality of life improved 27.5% (95% CI: 34.6-48.8 to 22.4-37.9; P = .0100).

CONCLUSION

Our results suggest that DBS of the fields of Forel improved motor symptoms in PD, as well as the FOG, falls, balance, postural instability, and quality of life.

Acute low frequency dorsal subthalamic nucleus stimulation improves verbal fluency in Parkinson's disease

BACKGROUND

Parkinson's disease (PD) is a common neurodegenerative disorder that results in movement-related dysfunction and has variable cognitive impairment. Deep brain stimulation (DBS) of the dorsal subthalamic nucleus (STN) has been shown to be effective in improving motor symptoms; however, cognitive impairment is often unchanged, and in some cases, worsened particularly on tasks of verbal fluency. Traditional DBS strategies use high frequency gamma stimulation for motor symptoms (∼130 Hz), but there is evidence that low frequency theta oscillations (5-12 Hz) are important in cognition.

METHODS

We tested the effects of stimulation frequency and location on verbal fluency among patients who underwent STN DBS implantation with externalized leads. During baseline cognitive testing, STN field potentials were recorded and the individual patients' peak theta frequency power was identified during each cognitive task. Patients repeated cognitive testing at five different stimulation settings: no stimulation, dorsal contact gamma (130 Hz), ventral contact gamma, dorsal theta (peak baseline theta) and ventral theta (peak baseline theta) frequency stimulation.

RESULTS

Acute left dorsal peak theta frequency STN stimulation improves overall verbal fluency compared to no stimulation and to either dorsal or ventral gamma stimulation. Stratifying by type of verbal fluency probes, verbal fluency in episodic categories was improved with dorsal theta stimulation compared to all other conditions, while there were no differences between stimulation conditions in non-episodic probe conditions.

CONCLUSION

Here, we provide evidence that dorsal STN theta stimulation may improve verbal fluency, suggesting a potential possibility of integrating theta stimulation into current DBS paradigms to improve cognitive outcomes.