Connectivity Predicts deep brain stimulation outcome in Parkinson disease

Brain network localization of gray matter atrophy, neurocognitive and social cognitive dysfunction in schizophrenia

BACKGROUND

Numerous studies have established the presence of gray matter atrophy and brain activation abnormalities during neurocognitive and social cognitive tasks in schizophrenia. Despite a growing consensus that diseases localize better to distributed brain networks than individual anatomical regions, there is still a dearth of literature examining brain network localization of gray matter atrophy, neurocognitive and social cognitive dysfunction in schizophrenia.

METHODS

To address this gap, we initially identified brain locations of structural and functional abnormalities in schizophrenia from 301 published neuroimaging studies with 8712 schizophrenia individuals and 9275 healthy controls. By applying novel functional connectivity network mapping to large-scale resting-state functional magnetic resonance imaging datasets, we mapped these affected brain locations to 3 brain abnormality networks of schizophrenia.

RESULTS

The gray matter atrophy network of schizophrenia comprised a broadly distributed set of brain areas predominantly implicating the ventral attention, somatomotor, and default networks. The neurocognitive dysfunction network was also composed of widespread brain areas primarily involving the frontoparietal and default networks. By contrast, the social cognitive dysfunction network consisted of circumscribed brain regions mainly implicating the default, subcortical, and visual networks.

CONCLUSIONS

Our findings suggest shared and unique brain network substrates of gray matter atrophy, neurocognitive and social cognitive dysfunction in schizophrenia, which may not only refine the understanding of disease neuropathology from a network perspective, but also potentially contribute to more targeted and effective treatments for impairments in different cognitive domains in schizophrenia.

Clinical neurophysiology in the treatment of movement disorders: IFCN handbook chapter

In this review, different aspects of the use of clinical neurophysiology techniques for the treatment of movement disorders are addressed. First of all, these techniques can be used to guide neuromodulation techniques or to perform therapeutic neuromodulation as such. Neuromodulation includes invasive techniques based on the surgical implantation of electrodes and a pulse generator, such as deep brain stimulation (DBS) or spinal cord stimulation (SCS) on the one hand, and non-invasive techniques aimed at modulating or even lesioning neural structures by transcranial application. Movement disorders are one of the main areas of indication for the various neuromodulation techniques. This review focuses on the following techniques: DBS, repetitive transcranial magnetic stimulation (rTMS), low-intensity transcranial electrical stimulation, including transcranial direct current stimulation (tDCS) and transcranial alternating current stimulation (tACS), and focused ultrasound (FUS), including high-intensity magnetic resonance-guided FUS (MRgFUS), and pulsed mode low-intensity transcranial FUS stimulation (TUS). The main clinical conditions in which neuromodulation has proven its efficacy are Parkinson's disease, dystonia, and essential tremor, mainly using DBS or MRgFUS. There is also some evidence for Tourette syndrome (DBS), Huntington's disease (DBS), cerebellar ataxia (tDCS), and axial signs (SCS) and depression (rTMS) in PD. The development of non-invasive transcranial neuromodulation techniques is limited by the short-term clinical impact of these techniques, especially rTMS, in the context of very chronic diseases. However, at-home use (tDCS) or current advances in the design of closed-loop stimulation (tACS) may open new perspectives for the application of these techniques in patients, favored by their easier use and lower rate of adverse effects compared to invasive or lesioning methods. Finally, this review summarizes the evidence for keeping the use of electromyography to optimize the identification of muscles to be treated with botulinum toxin injection, which is indicated and widely performed for the treatment of various movement disorders.

Linking Invasive and Noninvasive Brain Stimulation in Parkinson's Disease: A Randomized Trial

BACKGROUND

Recent imaging studies identified a brain network associated with clinical improvement following deep brain stimulation (DBS) in Parkinson's disease (PD), the PD response network.

OBJECTIVES

This study aimed to assess the impact of neuromodulation on PD motor symptoms by targeting this network noninvasively using multifocal transcranial direct current stimulation (tDCS).

METHODS

In a prospective, randomized, double-blinded, crossover trial, 21 PD patients (mean age 59.7 years, mean Hoehn & Yahr [H&Y] 2.4) received multifocal tDCS targeting the a-priori network. Twenty-minute sessions of tDCS and sham were administered on 2 days in randomized order. Movement Disorder Society-Unified Parkinson's Disease Rating Scale-Part III (MDS-UPDRS-III) scores were assessed.

RESULTS

Before intervention, MDS-UPDRS-III scores were comparable in both conditions (stimulation days: 37.38 (standard deviation [SD] = 12.50, confidence interval [CI] = 32.04, 42.73) vs. sham days: 36.95 (SD = 13.94, CI = 30.99, 42.91), P = 0.63). Active stimulation resulted in a reduction by 3.6 points (9.7%) to 33.76 (SD = 11.19, CI = 28.98, 38.55) points, whereas no relevant change was observed after sham stimulation (36.43 [SD = 14.15, CI = 30.38, 42.48], average improvement: 0.5 [1.4%]). Repeated-measures analysis of variance (ANOVA) confirmed significance (main effect of time: F(1,20)=4.35, P < 0.05). Tukey's post hoc tests indicated MDS-UPDRS-III improvement after active stimulation (t [20] = 2.9, P = 0.03) but not after sham (t [20] = 0.42, P > 0.05). In a subset of patients that underwent DBS surgery later, their DBS response correlated with tDCS effects (R = 0.55, P(1) = 0.04).

CONCLUSION

Noninvasive, multifocal tDCS targeting a DBS-derived network significantly improved PD motor symptoms. Despite a small effect size, this study provides proof of principle for the successful noninvasive neuromodulation of an invasively identified network. Future studies should investigate repeated tDCS sessions and their utility for screening before DBS surgery. © 2024 The Author(s). Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Centromedian region thalamic responsive neurostimulation mitigates idiopathic generalized and multifocal epilepsy with focal to bilateral tonic-clonic seizures

OBJECTIVE

Although >30% of epilepsy patients have drug-resistant epilepsy (DRE), typically those with generalized or multifocal disease have not traditionally been considered surgical candidates. Responsive neurostimulation (RNS) of the centromedian (CM) region of the thalamus now appears to be a promising therapeutic option for this patient population. We present outcomes following CM RNS for 13 patients with idiopathic generalized epilepsy (IGE) and eight with multifocal onsets that rapidly generalize to bilateral tonic-clonic (focal to bilateral tonic-clonic [FBTC]) seizures.

METHODS

A retrospective review of all patients undergoing bilateral CM RNS by the senior author through July 2022 were reviewed. Electrodes were localized and volumes of tissue activation were modeled in Lead-DBS. Changes in patient seizure frequency were extracted from electronic medical records.

RESULTS

Twenty-one patients with DRE underwent bilateral CM RNS implantation. For 17 patients with at least 1 year of postimplantation follow-up, average seizure reduction from preoperative baseline was 82.6% (SD = 19.0%, median = 91.7%), with 18% of patients Engel class 1, 29% Engel class 2, 53% Engel class 3, and 0% Engel class 4. There was a trend for average seizure reduction to be greater for patients with nonlesional FBTC seizures than for other patients. For patients achieving at least Engel class 3 outcome, median time to worthwhile seizure reduction was 203.5 days (interquartile range = 110.5-343.75 days). Patients with IGE with myoclonic seizures had a significantly shorter time to worthwhile seizure reduction than other patients. The surgical targeting strategy evolved after the first four subjects to achieve greater anatomic accuracy.

SIGNIFICANCE

Patients with both primary and rapidly generalized epilepsy who underwent CM RNS experienced substantial seizure relief. Subsets of these patient populations may particularly benefit from CM RNS. The refinement of lead targeting, tuning of RNS system parameters, and patient selection are ongoing areas of investigation.

A reproducible pipeline for parcellation of the anterior limb of the internal capsule

BACKGROUND

The anterior limb of the internal capsule (ALIC) is a white matter structure connecting the prefrontal cortex (PFC) to the brainstem, thalamus, and subthalamic nucleus. It is a target for deep brain stimulation (DBS) for obsessive-compulsive disorder. There is strong interest in improving DBS targeting by using diffusion tractography to reconstruct and target specific ALIC fiber pathways, but this methodology is susceptible to errors and lacks validation. To address these limitations, we developed a novel diffusion tractography pipeline that generates reliable and biologically validated ALIC white matter reconstructions.

METHODS

Following algorithm development and refinement, we analyzed 43 control subjects each with 2 sets of 3T MRI data and a subset of 5 controls with 7T data from the Human Connectome Project. We generated 22 segmented ALIC fiber bundles (11 per hemisphere) based on prefrontal PFC regions of interest, and we analyzed the relationships among bundles.

RESULTS

We successfully reproduced the topographies established by prior anatomical work using images acquired at both 3T and 7T. Quantitative assessment demonstrated significantly smaller intra-subject variability relative to inter-subject variability for both test and retest groups across all but one PFC region. We examined the overlap between fibers from different PFC regions and a response tract for obsessive-compulsive disorder deep brain stimulation, and we reconstructed the PFC hyperdirect pathway using a modified version of our pipeline.

DISCUSSION

Our dMRI algorithm reliably generates biologically validated ALIC white matter reconstructions, allowing for more precise modelling of fibers for neuromodulation therapies.

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.

Tractography-Based Modeling Explains Treatment Outcomes in Patients Undergoing Deep Brain Stimulation for Obsessive-Compulsive Disorder

BACKGROUND

Deep brain stimulation (DBS) is an established and expanding therapy for treatment-refractory obsessive-compulsive disorder. Previous work has suggested that a white matter circuit providing hyperdirect input from the dorsal cingulate and ventrolateral prefrontal regions to the subthalamic nucleus could be an effective neuromodulatory target.

METHODS

We tested this concept by attempting to retrospectively explain through predictive modeling the ranks of clinical improvement as measured by the Yale-Brown Obsessive Compulsive Scale (Y-BOCS) in 10 patients with obsessive-compulsive disorder who underwent DBS to the ventral anterior limb of internal capsule with subsequent programming uninformed by the putative target tract.

RESULTS

Rank predictions were carried out using the tract model by a team that was completely uninvolved in DBS planning and programming. Predicted Y-BOCS improvement ranks significantly correlated with actual Y-BOCS improvement ranks at the 6-month follow-up (r = 0.75, p = .013). Predicted score improvements correlated with actual Y-BOCS score improvements (r = 0.72, p = .018).

CONCLUSIONS

Here, we provide data in a first-of-its-kind report suggesting that normative tractography-based modeling can blindly predict treatment response in DBS for obsessive-compulsive disorder.

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.

Individual Structural Covariance Network Predicts Long-Term Motor Improvement in Parkinson Disease with Subthalamic Nucleus Deep Brain Stimulation

BACKGROUND AND PURPOSE

The efficacy of long-term chronic subthalamic nucleus deep brain stimulation (STN-DBS) in treating Parkinson disease (PD) exhibits substantial variability among individuals. The preoperative identification of suitable deep brain stimulation (DBS) candidates through predictive means becomes crucial. Our study aims to investigate the predictive value of characterizing individualized structural covariance networks for long-term efficacy of DBS, offering patients a precise and cost-effective preoperative screening tool.

MATERIALS AND METHODS

We included 138 patients with PD and 40 healthy controls. We developed individualized structural covariance networks from T1-weighted images utilizing network template perturbation, and computed the networks' topological characteristics. Patients were categorized according to their long-term motor improvement following STN-DBS. Intergroup analyses were conducted on individual network edges and topological indices, alongside correlation analyses with long-term outcomes for the entire patient cohort. Finally, machine learning algorithms were employed for regression and classification to predict post-DBS motor improvement.

RESULTS

Among the patients with PD, 6 edges (left middle frontal and left caudate nucleus, right olfactory and right insula, left superior medial frontal gyrus and right insula, right middle frontal and left paracentral lobule, right middle frontal and cerebellum, left lobule VIIb of the cerebellum and the vermis of the cerebellum) exhibited significant results in intergroup comparisons and correlation analyses. Increased degree centrality and local efficiency of the cerebellum, parahippocampal gyrus, and postcentral gyrus were associated with DBS improvement. A regression model constructed from these 6 edges revealed a significant correlation between predicted and observed changes in the unified PD rating scale (R = 0.671, P < .001) and receiver operating characteristic analysis demonstrated an area under the curve of 0.802, effectively distinguishing between patients with good and moderate improvement post-DBS.

CONCLUSIONS

Our findings reveal the link between individual structural covariance network fingerprints in patients with PD and long-term motor outcome following STN-DBS. Additionally, binary and continuous cerebellum-basal ganglia-frontal structural covariance network edges have emerged as potential predictive biomarkers for DBS motor outcome.

Individualized Structural Perturbations on Normative Brain Connectome Restrict Deep Brain Stimulation Outcomes in Parkinson's Disease

BACKGROUND

Patients with Parkinson's disease (PD) respond to deep brain stimulation (DBS) variably. However, how brain substrates restrict DBS outcomes remains unclear.

OBJECTIVE

In this article, we aim to identify prognostic brain signatures for explaining the response variability.

METHODS

We retrospectively investigated a cohort of patients with PD (n = 141) between 2017 and 2022, and defined DBS outcomes as the improvement ratio of clinical motor scores. We used a deviation index to quantify individual perturbations on a reference structural covariance network acquired with preoperative T1-weighted magnetic resonance imaging. The neurobiological perturbations of patients were represented as z scored indices based on the chronological perturbations measured on a group of normal aging adults.

RESULTS

After applying stringent statistical tests (z > 2.5) and correcting for false discoveries (P < 0.01), we found that accelerated deviations mainly affected the prefrontal cortex, motor strip, limbic system, and cerebellum in PD. Particularly, a negative network within the accelerated deviations, expressed as "more preoperative deviations, less postoperative improvements," could predict DBS outcomes (mean absolute error = 0.09, R2 = 0.15). Moreover, a fusion of personal brain predictors and medical responses significantly improved traditional evaluations of DBS outcomes. Notably, the most important brain predictor, a pathway connecting the cognitive unit (prefrontal cortex) and motor control unit (cerebellum and motor strip), partially mediates DBS outcomes with the age at surgery.

CONCLUSIONS

Our findings suggest that individual structural perturbations on the cognitive motor control circuit are critical for modulating DBS outcomes. Interventions toward the circuit have the potential for additional clinical improvements. © 2024 The Author(s). Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Brain Structural and Functional Damage Network Localization of Suicide

BACKGROUND

Extensive neuroimaging research on brain structural and functional correlates of suicide has produced inconsistent results. Despite increasing recognition that damage in multiple different brain locations that causes the same symptom can map to a common brain network, there is still a paucity of research investigating network localization of suicide.

METHODS

To clarify this issue, we initially identified brain structural and functional damage locations in relation to suicide from 63 published studies with 2135 suicidal and 2606 nonsuicidal individuals. By applying novel functional connectivity network mapping to large-scale discovery and validation resting-state functional magnetic resonance imaging datasets, we mapped these affected brain locations to 3 suicide brain damage networks corresponding to different imaging modalities.

RESULTS

The suicide gray matter volume damage network comprised widely distributed brain areas primarily involving the dorsal default mode, basal ganglia, and anterior salience networks. The suicide task-induced activation damage network was similar to but less extensive than the gray matter volume damage network, predominantly implicating the same canonical networks. The suicide resting-state activity damage network manifested as a localized set of brain regions encompassing the orbitofrontal cortex and middle cingulate cortex.

CONCLUSIONS

Our findings not only may help reconcile prior heterogeneous neuroimaging results, but also may provide insights into the neurobiological mechanisms of suicide from a network perspective, which may ultimately inform more targeted and effective strategies to prevent suicide.

Fronto-thalamic networks and the left ventral thalamic nuclei play a key role in aphasia after thalamic stroke

Thalamic aphasia results from focal thalamic lesions that cause dysfunction of remote but functionally connected cortical areas due to language network perturbation. However, specific local and network-level neural substrates of thalamic aphasia remain incompletely understood. Using lesion symptom mapping, we demonstrate that lesions in the left ventrolateral and ventral anterior thalamic nucleus are most strongly associated with aphasia in general and with impaired semantic and phonemic fluency and complex comprehension in particular. Lesion network mapping (using a normative connectome based on fMRI data from 1000 healthy individuals) reveals a Thalamic aphasia network encompassing widespread left-hemispheric cerebral connections, with Broca's area showing the strongest associations, followed by the superior and middle frontal gyri, precentral and paracingulate gyri, and globus pallidus. Our results imply the critical involvement of the left ventrolateral and left ventral anterior thalamic nuclei in engaging left frontal cortical areas, especially Broca's area, during language processing.

Localization of stuttering based on causal brain lesions

Stuttering affects approximately 1 in 100 adults and can result in significant communication problems and social anxiety. It most often occurs as a developmental disorder but can also be caused by focal brain damage. These latter cases may lend unique insight into the brain regions causing stuttering. Here, we investigated the neuroanatomical substrate of stuttering using three independent datasets: (i) case reports from the published literature of acquired neurogenic stuttering following stroke (n = 20, 14 males/six females, 16-77 years); (ii) a clinical single study cohort with acquired neurogenic stuttering following stroke (n = 20, 13 males/seven females, 45-87 years); and (iii) adults with persistent developmental stuttering (n = 20, 14 males/six females, 18-43 years). We used the first two datasets and lesion network mapping to test whether lesions causing acquired stuttering map to a common brain network. We then used the third dataset to test whether this lesion-based network was relevant to developmental stuttering. In our literature dataset, we found that lesions causing stuttering occurred in multiple heterogeneous brain regions, but these lesion locations were all functionally connected to a common network centred around the left putamen, including the claustrum, amygdalostriatal transition area and other adjacent areas. This finding was shown to be specific for stuttering (PFWE < 0.05) and reproducible in our independent clinical cohort of patients with stroke-induced stuttering (PFWE < 0.05), resulting in a common acquired stuttering network across both stroke datasets. Within the common acquired stuttering network, we found a significant association between grey matter volume and stuttering impact for adults with persistent developmental stuttering in the left posteroventral putamen, extending into the adjacent claustrum and amygdalostriatal transition area (PFWE < 0.05). We conclude that lesions causing acquired neurogenic stuttering map to a common brain network, centred to the left putamen, claustrum and amygdalostriatal transition area. The association of this lesion-based network with symptom severity in developmental stuttering suggests a shared neuroanatomy across aetiologies.

Somatotopy of the sensory thalamus: inputs from directional deep brain stimulation in pain patients

OBJECTIVE

The sensory ventroposterior (VP) thalamic nuclei display a mediolateral somatotopic organization (respectively head, arm, and leg). We studied this somatotopy using directional VP deep brain stimulation (DBS) in patients treated for chronic neuropathic pain.

METHODS

Six patients with central (four) or peripheral (two) neuropathic pain were treated by VP DBS using directional leads in a prospective study (clinicaltrials.gov NCT03399942). Lead-DBS toolbox was used for leads localization, visualization, and modeling of the volume of tissue activated (VTA). Stimulation was delivered in each direction, 1 month after surgery and correlated to the location of stimulation-induced paresthesias. The somatotopy was modeled by correlating the respective locations of paresthesias and VTAs. We recorded 48 distinct paresthesia maps corresponding to 48 VTAs (including 36 related to directional stimulation).

RESULTS

We observed that, in each patient, respective body representations of the trunk, upper limb, lower limb, and head were closely located around the lead. These representations differed across patients, did not follow a common organization and were not concordant with the previously described somatotopic organization of the sensory thalamus.

INTERPRETATION

Thalamic reorganization has been reported in chronic pain patients compared to non-pain patients operated for movement disorders in previous studies using intraoperative recordings and micro-stimulation. Using a different methodology, namely 3D representation of the VTA by the directional postoperative stimulation through a stationary electrode, our study brings additional arguments in favor of a reorganization of the VP thalamic somatotopy in patients suffering from chronic neuropathic pain of central or peripheral origin.

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.

Electrophysiological sweet spot mapping in deep brain stimulation for Parkinson's disease patients

BACKGROUND

Subthalamic deep brain stimulation (STN-DBS) is a well-established therapy to treat Parkinson's disease (PD). However, the STN-DBS sub-target remains debated. Recently, a white matter tract termed the hyperdirect pathway (HDP), directly connecting the motor cortex to STN, has gained interest as HDP stimulation is hypothesized to drive DBS therapeutic effects. Previously, we have investigated EEG-based evoked potentials (EPs) to better understand the neuroanatomical origins of the DBS clinical effect. We found a 3-ms peak (P3) relating to clinical benefit, and a 10-ms peak (P10) suggesting nigral side effects. Here, we aimed to investigate the neuroanatomical origins of DBS EPs using probabilistic mapping.

METHODS

EPs were recorded using EEG whilst low-frequency stimulation was delivered at all DBS-contacts individually. Next, EPs were mapped onto the patients' individual space and then transformed to MNI standard space. Using voxel-wise and fiber-wise probabilistic mapping, we determined hotspots/hottracts and coldspots/coldtracts for P3 and P10. Topography analysis was also performed to determine the spatial distribution of the DBS EPs.

RESULTS

In all 13 patients (18 hemispheres), voxel- and fiber-wise probabilistic mapping resulted in a P3-hotspot/hottract centered on the posterodorsomedial STN border indicative of HDP stimulation, while the P10-hotspot/hottract covered large parts of the substantia nigra.

CONCLUSION

This study investigated EP-based probabilistic mapping in PD patients during STN-DBS, revealing a P3-hotspot/hottract in line with HDP stimulation and P10-hotspot/hottract related to nigral stimulation. Results from this study provide key evidence for an electrophysiological measure of HDP and nigral stimulation.

Subthalamic nucleus-language network connectivity predicts dopaminergic modulation of speech function in Parkinson's disease

Speech impediments are a prominent yet understudied symptom of Parkinson's disease (PD). While the subthalamic nucleus (STN) is an established clinical target for treating motor symptoms, these interventions can lead to further worsening of speech. The interplay between dopaminergic medication, STN circuitry, and their downstream effects on speech in PD is not yet fully understood. Here, we investigate the effect of dopaminergic medication on STN circuitry and probe its association with speech and cognitive functions in PD patients. We found that changes in intrinsic functional connectivity of the STN were associated with alterations in speech functions in PD. Interestingly, this relationship was characterized by altered functional connectivity of the dorsolateral and ventromedial subdivisions of the STN with the language network. Crucially, medication-induced changes in functional connectivity between the STN's dorsolateral subdivision and key regions in the language network, including the left inferior frontal cortex and the left superior temporal gyrus, correlated with alterations on a standardized neuropsychological test requiring oral responses. This relation was not observed in the written version of the same test. Furthermore, changes in functional connectivity between STN and language regions predicted the medication's downstream effects on speech-related cognitive performance. These findings reveal a previously unidentified brain mechanism through which dopaminergic medication influences speech function in PD. Our study sheds light into the subcortical-cortical circuit mechanisms underlying impaired speech control in PD. The insights gained here could inform treatment strategies aimed at mitigating speech deficits in PD and enhancing the quality of life for affected individuals.

Engaging dystonia networks with subthalamic stimulation

Deep brain stimulation is a viable and efficacious treatment option for dystonia. While the internal pallidum serves as the primary target, more recently, stimulation of the subthalamic nucleus (STN) has been investigated. However, optimal targeting within this structure and its complex surroundings have not been studied in depth. Indeed, multiple historical targets that have been used for surgical treatment of dystonia are directly adjacent to the STN. Further, multiple types of dystonia exist, and outcomes are variable, suggesting that not all types would profit maximally from the exact same target. Therefore, a thorough investigation of the neural substrates underlying effects on dystonia symptoms is warranted. Here, we analyze a multi-center cohort of isolated dystonia patients with subthalamic implantations (N = 58) and relate their stimulation sites to improvement of appendicular and cervical symptoms as well as blepharospasm. Stimulation of the ventral oral posterior nucleus of thalamus and surrounding regions was associated with improvement in cervical dystonia, while stimulation of the dorsolateral STN was associated with improvement in limb dystonia and blepharospasm. This dissociation was also evident for structural connectivity, where the cerebellothalamic, corticospinal and pallidosubthalamic tracts were associated with improvement of cervical dystonia, while hyperdirect and subthalamopallidal pathways were associated with alleviation of limb dystonia and blepharospasm. Importantly, a single well-placed electrode may reach the three optimal target sites. On the level of functional networks, improvement of limb dystonia was correlated with connectivity to the corresponding somatotopic regions in primary motor cortex, while alleviation of cervical dystonia was correlated with connectivity to the recently described 'action-mode' network that involves supplementary motor and premotor cortex. Our findings suggest that different types of dystonia symptoms are modulated via distinct networks. Namely, appendicular dystonia and blepharospasm are improved with modulation of the basal ganglia, and, in particular, the subthalamic circuitry, including projections from the primary motor cortex. In contrast, cervical dystonia was more responsive when engaging the cerebello-thalamo-cortical circuit, including direct stimulation of ventral thalamic nuclei. These findings may inform DBS targeting and image-based programming strategies for patient-specific treatment of dystonia.

Motor network dynamic resting state fMRI connectivity of neurotypical children in regions affected by cerebral palsy

Background

Normative childhood motor network resting-state fMRI effective connectivity is undefined, yet necessary for translatable dynamic resting-state-network-informed evaluation in pediatric cerebral palsy.

Methods

Cross-spectral dynamic causal modeling of resting-state-fMRI was investigated in 50 neurotypically developing 5- to 13-year-old children. Fully connected six-node network models per hemisphere included primary motor cortex, striatum, subthalamic nucleus, globus pallidus internus, thalamus, and contralateral cerebellum. Parametric Empirical Bayes with exhaustive Bayesian model reduction and Bayesian modeling averaging informed the model; Purdue Pegboard Test scores of hand motor behavior were the covariate at the group level to determine the effective-connectivity-functional behavior relationship.

Results

Although both hemispheres exhibited similar effective connectivity of motor cortico-basal ganglia-cerebellar networks, magnitudes were slightly greater on the right, except for left-sided connections of the striatum which were more numerous and of opposite polarity. Inter-nodal motor network effective connectivity remained consistent and robust across subjects. Age had a greater impact on connections to the contralateral cerebellum, bilaterally. Motor behavior, however, affected different connections in each hemisphere, exerting a more prominent effect on the left modulatory connections to the subthalamic nucleus, contralateral cerebellum, primary motor cortex, and thalamus.

Discussion

This study revealed a consistent pattern of directed resting-state effective connectivity in healthy children aged 5-13 years within the motor network, encompassing cortical, subcortical, and cerebellar regions, correlated with motor skill proficiency. Both hemispheres exhibited similar effective connectivity within motor cortico-basal ganglia-cerebellar networks reflecting inter-nodal signal direction predicted by other modalities, mainly differing from task-dependent studies due to network differences at rest. Notably, age-related changes were more pronounced in connections to the contralateral cerebellum. Conversely, motor behavior distinctly impacted connections in each hemisphere, emphasizing its role in modulating left sided connections to the subthalamic nucleus, contralateral cerebellum, primary motor cortex, and thalamus. Motor network effective connectivity was correlated with motor behavior, validating its physiological significance. This study is the first to evaluate a normative effective connectivity model for the pediatric motor network using resting-state functional MRI correlating with behavior and serves as a foundation for identifying abnormal findings and optimizing targeted interventions like deep brain stimulation, potentially influencing future therapeutic approaches for children with movement disorders.

Postoperative cerebellar mutism syndrome is an acquired autism-like network disturbance

BACKGROUND

Cerebellar mutism syndrome (CMS) is a common and debilitating complication of posterior fossa tumor surgery in children. Affected children exhibit communication and social impairments that overlap phenomenologically with subsets of deficits exhibited by children with Autism spectrum disorder (ASD). Although both CMS and ASD are thought to involve disrupted cerebro-cerebellar circuitry, they are considered independent conditions due to an incomplete understanding of their shared neural substrates.

METHODS

In this study, we analyzed postoperative cerebellar lesions from 90 children undergoing posterior fossa resection of medulloblastoma, 30 of whom developed CMS. Lesion locations were mapped to a standard atlas, and the networks functionally connected to each lesion were computed in normative adult and pediatric datasets. Generalizability to ASD was assessed using an independent cohort of children with ASD and matched controls (n = 427).

RESULTS

Lesions in children who developed CMS involved the vermis and inferomedial cerebellar lobules. They engaged large-scale cerebellothalamocortical circuits with a preponderance for the prefrontal and parietal cortices in the pediatric and adult connectomes, respectively. Moreover, with increasing connectomic age, CMS-associated lesions demonstrated stronger connectivity to the midbrain/red nuclei, thalami and inferior parietal lobules and weaker connectivity to the prefrontal cortex. Importantly, the CMS-associated lesion network was independently reproduced in ASD and correlated with communication and social deficits, but not repetitive behaviors.

CONCLUSIONS

Our findings indicate that CMS-associated lesions may result in an ASD-like network disturbance that occurs during sensitive windows of brain development. A common network disturbance between CMS and ASD may inform improved treatment strategies for affected children.

Personalizing Deep Brain Stimulation Therapy for Parkinson's Disease With Whole-Brain MRI Radiomics and Machine Learning

Background Deep brain stimulation (DBS) is a well-recognised treatment for advanced Parkinson's disease (PD) patients. Structural brain alterations of the white matter can correlate with disease progression and act as a biomarker for DBS therapy outcomes. This study aims to develop a machine learning-driven predictive model for DBS patient selection using whole-brain white matter radiomics and common clinical variables. Methodology A total of 120 PD patients underwent DBS of the subthalamic nucleus. Their therapy effect was assessed at the one-year follow-up with the Unified Parkinson's Disease Rating Scale-part III (UPDRSIII) motor component. Radiomics analysis of whole-brain white matter was performed with PyRadiomics. The following machine learning methods were used: logistic regression (LR), support vector machine, naïve Bayes, K-nearest neighbours, and random forest (RF) to allow prediction of clinically meaningful UPRDSIII motor response before and after. Clinical variables were also added to the model to improve accuracy. Results The RF model showed the best performance on the final whole dataset with an area under the curve (AUC) of 0.99, accuracy of 0.95, sensitivity of 0.93, and specificity of 0.97. At the same time, the LR model showed an AUC of 0.93, accuracy of 0.88, sensitivity of 0.84, and specificity of 0.91. Conclusions Machine learning models can be used in clinical decision support tools which can deliver true personalised therapy recommendations for PD patients. Clinicians and engineers should choose between best-performing, less interpretable models vs. most interpretable, lesser-performing models. Larger clinical trials would allow to build trust among clinicians and patients to widely use these AI tools in the future.

Clinical and Brain Morphometry Predictors of Deep Brain Stimulation Outcome in Parkinson's Disease

Subthalamic deep brain stimulation (STN-DBS) is known to improve motor function in advanced Parkinson's disease (PD) and to enable a reduction of anti-parkinsonian medication. While the levodopa challenge test and disease duration are considered good predictors of STN-DBS outcome, other clinical and neuroanatomical predictors are less established. This study aimed to evaluate, in addition to clinical predictors, the effect of patients' individual brain topography on DBS outcome. The medical records of 35 PD patients were used to analyze DBS outcomes measured with the following scales: Part III of the Unified Parkinson's Disease Rating Scale (UPDRS-III) off medication at baseline, and at 6-months during medication off and stimulation on, use of anti-parkinsonian medication (LED), Abnormal Involuntary Movement Scale (AIMS) and Non-Motor Symptoms Questionnaire (NMS-Quest). Furthermore, preoperative brain MRI images were utilized to analyze the brain morphology in relation to STN-DBS outcome. With STN-DBS, a 44% reduction in the UPDRS-III score and a 43% decrease in the LED were observed (p<0.001). Dyskinesia and non-motor symptoms decreased significantly [median reductions of 78,6% (IQR 45,5%) and 18,4% (IQR 32,2%) respectively, p=0.001 - 0.047]. Along with the levodopa challenge test, patients' age correlated with the observed DBS outcome measured as UPDRS-III improvement (ρ= -0.466 - -0.521, p<0.005). Patients with greater LED decline had lower grey matter volumes in left superior medial frontal gyrus, in supplementary motor area and cingulum bilaterally. Additionally, patients with greater UPDRS-III score improvement had lower grey matter volume in similar grey matter areas. These findings remained significant when adjusted for sex, age, baseline LED and UPDRS scores respectively and for total intracranial volume (p=0.0041- 0.001). However, only the LED decrease finding remained significant when the analyses were further controlled for stimulation amplitude. It appears that along with the clinical predictors of STN-DBS outcome, individual patient topographic differences may influence DBS outcome. Clinical Trial Registration Number: NCT06095245, registration date October 23, 2023, retrospectively registered.

Enhancing Cognitive Performance Prediction through White Matter Hyperintensity Connectivity Assessment: A Multicenter Lesion Network Mapping Analysis of 3,485 Memory Clinic Patients

Introduction

White matter hyperintensities of presumed vascular origin (WMH) are associated with cognitive impairment and are a key imaging marker in evaluating cognitive health. However, WMH volume alone does not fully account for the extent of cognitive deficits and the mechanisms linking WMH to these deficits remain unclear. We propose that lesion network mapping (LNM), enables to infer if brain networks are connected to lesions, and could be a promising technique for enhancing our understanding of the role of WMH in cognitive disorders. Our study employed this approach to test the following hypotheses: (1) LNM-informed markers surpass WMH volumes in predicting cognitive performance, and (2) WMH contributing to cognitive impairment map to specific brain networks.

Methods & results

We analyzed cross-sectional data of 3,485 patients from 10 memory clinic cohorts within the Meta VCI Map Consortium, using harmonized test results in 4 cognitive domains and WMH segmentations. WMH segmentations were registered to a standard space and mapped onto existing normative structural and functional brain connectome data. We employed LNM to quantify WMH connectivity across 480 atlas-based gray and white matter regions of interest (ROI), resulting in ROI-level structural and functional LNM scores. The capacity of total and regional WMH volumes and LNM scores in predicting cognitive function was compared using ridge regression models in a nested cross-validation. LNM scores predicted performance in three cognitive domains (attention and executive function, information processing speed, and verbal memory) significantly better than WMH volumes. LNM scores did not improve prediction for language functions. ROI-level analysis revealed that higher LNM scores, representing greater disruptive effects of WMH on regional connectivity, in gray and white matter regions of the dorsal and ventral attention networks were associated with lower cognitive performance.

Conclusion

Measures of WMH-related brain network connectivity significantly improve the prediction of current cognitive performance in memory clinic patients compared to WMH volume as a traditional imaging marker of cerebrovascular disease. This highlights the crucial role of network effects, particularly in attentionrelated brain regions, improving our understanding of vascular contributions to cognitive impairment. Moving forward, refining WMH information with connectivity data could contribute to patient-tailored therapeutic interventions and facilitate the identification of subgroups at risk of cognitive disorders.

Modeling the volume of tissue activated in deep brain stimulation and its clinical influence: a review

Deep brain stimulation (DBS) is a neuromodulatory therapy that has been FDA approved for the treatment of various disorders, including but not limited to, movement disorders (e.g., Parkinson's disease and essential tremor), epilepsy, and obsessive-compulsive disorder. Computational methods for estimating the volume of tissue activated (VTA), coupled with brain imaging techniques, form the basis of models that are being generated from retrospective clinical studies for predicting DBS patient outcomes. For instance, VTA models are used to generate target-and network-based probabilistic stimulation maps that play a crucial role in predicting DBS treatment outcomes. This review defines the methods for calculation of tissue activation (or modulation) including ones that use heuristic and clinically derived estimates and more computationally involved ones that rely on finite-element methods and biophysical axon models. We define model parameters and provide a comparison of commercial, open-source, and academic simulation platforms available for integrated neuroimaging and neural activation prediction. In addition, we review clinical studies that use these modeling methods as a function of disease. By describing the tissue-activation modeling methods and highlighting their application in clinical studies, we provide the neural engineering and clinical neuromodulation communities with perspectives that may influence the adoption of modeling methods for future DBS studies.

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

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

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

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

Neuroscience fundamentals relevant to neuromodulation: Neurobiology of deep brain stimulation in Parkinson's disease

Deep Brain Stimulation (DBS) has become a pivotal therapeutic approach for Parkinson's Disease (PD) and various neuropsychiatric conditions, impacting over 200,000 patients. Despite its widespread application, the intricate mechanisms behind DBS remain a subject of ongoing investigation. This article provides an overview of the current knowledge surrounding the local, circuit, and neurobiochemical effects of DBS, focusing on the subthalamic nucleus (STN) as a key target in PD management. The local effects of DBS, once thought to mimic a reversible lesion, now reveal a more nuanced interplay with myelinated axons, neurotransmitter release, and the surrounding microenvironment. Circuit effects illuminate the modulation of oscillatory activities within the basal ganglia and emphasize communication between the STN and the primary motor cortex. Neurobiochemical effects, encompassing changes in dopamine levels and epigenetic modifications, add further complexity to the DBS landscape. Finally, within the context of understanding the mechanisms of DBS in PD, the article highlights the controversial question of whether DBS exerts disease-modifying effects in PD. While preclinical evidence suggests neuroprotective potential, clinical trials such as EARLYSTIM face challenges in assessing long-term disease modification due to enrollment timing and methodology limitations. The discussion underscores the need for robust biomarkers and large-scale prospective trials to conclusively determine DBS's potential as a disease-modifying therapy in PD.

A Systematic Review of Neurophysiology-Based Localization Techniques Used in Deep Brain Stimulation Surgery of the Subthalamic Nucleus

OBJECTIVE

This systematic review is conducted to identify, compare, and analyze neurophysiological feature selection, extraction, and classification to provide a comprehensive reference on neurophysiology-based subthalamic nucleus (STN) localization.

MATERIALS AND METHODS

The review was carried out using the methods and guidelines of the Kitchenham systematic review and provides an in-depth analysis on methods proposed on STN localization discussed in the literature between 2000 and 2021. Three research questions were formulated, and 115 publications were identified to answer the questions.

RESULTS

The three research questions formulated are answered using the literature found on the respective topics. This review discussed the technologies used in past research, and the performance of the state-of-the-art techniques is also reviewed.

CONCLUSION

This systematic review provides a comprehensive reference on neurophysiology-based STN localization by reviewing the research questions other new researchers may also have.

Biophysical Principles and Computational Modeling of Deep Brain Stimulation

BACKGROUND

Deep brain stimulation (DBS) has revolutionized the treatment of neurological disorders, yet the mechanisms of DBS are still under investigation. Computational models are important in silico tools for elucidating these underlying principles and potentially for personalizing DBS therapy to individual patients. The basic principles underlying neurostimulation computational models, however, are not well known in the clinical neuromodulation community.

OBJECTIVE

In this study, we present a tutorial on the derivation of computational models of DBS and outline the biophysical contributions of electrodes, stimulation parameters, and tissue substrates to the effects of DBS.

RESULTS

Given that many aspects of DBS are difficult to characterize experimentally, computational models have played an important role in understanding how material, size, shape, and contact segmentation influence device biocompatibility, energy efficiency, the spatial spread of the electric field, and the specificity of neural activation. Neural activation is dictated by stimulation parameters including frequency, current vs voltage control, amplitude, pulse width, polarity configurations, and waveform. These parameters also affect the potential for tissue damage, energy efficiency, the spatial spread of the electric field, and the specificity of neural activation. Activation of the neural substrate also is influenced by the encapsulation layer surrounding the electrode, the conductivity of the surrounding tissue, and the size and orientation of white matter fibers. These properties modulate the effects of the electric field and determine the ultimate therapeutic response.

CONCLUSION

This article describes biophysical principles that are useful for understanding the mechanisms of neurostimulation.

Linking connectivity of deep brain stimulation of nucleus accumbens area with clinical depression improvements: a retrospective longitudinal case series

Treatment-resistant depression is a severe form of major depressive disorder and deep brain stimulation is currently an investigational treatment. The stimulation's therapeutic effect may be explained through the functional and structural connectivities between the stimulated area and other brain regions, or to depression-associated networks. In this longitudinal, retrospective study, four female patients with treatment-resistant depression were implanted for stimulation in the nucleus accumbens area at our center. We analyzed the structural and functional connectivity of the stimulation area: the structural connectivity was investigated with probabilistic tractography; the functional connectivity was estimated by combining patient-specific stimulation volumes and a normative functional connectome. These structural and functional connectivity profiles were then related to four clinical outcome scores. At 1-year follow-up, the remission rate was 66%. We observed a consistent structural connectivity to Brodmann area 25 in the patient with the longest remission phase. The functional connectivity analysis resulted in patient-specific R-maps describing brain areas significantly correlated with symptom improvement in this patient, notably the prefrontal cortex. But the connectivity analysis was mixed across patients, calling for confirmation in a larger cohort and over longer time periods.

Diffusion and functional MRI in surgical neuromodulation

Surgical neuromodulation has witnessed significant progress in recent decades. Notably, deep brain stimulation (DBS), delivered precisely within therapeutic targets, has revolutionized the treatment of medication-refractory movement disorders and is now expanding for refractory psychiatric disorders, refractory epilepsy, and post-stroke motor recovery. In parallel, the advent of incisionless treatment with focused ultrasound ablation (FUSA) can offer patients life-changing symptomatic relief. Recent research has underscored the potential to further optimize DBS and FUSA outcomes by conceptualizing the therapeutic targets as critical nodes embedded within specific brain networks instead of strictly anatomical structures. This paradigm shift was facilitated by integrating two imaging modalities used regularly in brain connectomics research: diffusion MRI (dMRI) and functional MRI (fMRI). These advanced imaging techniques have helped optimize the targeting and programming techniques of surgical neuromodulation, all while holding immense promise for investigations into treating other neurological and psychiatric conditions. This review aims to provide a fundamental background of advanced imaging for clinicians and scientists, exploring the synergy between current and future approaches to neuromodulation as they relate to dMRI and fMRI capabilities. Focused research in this area is required to optimize existing, functional neurosurgical treatments while serving to build an investigative infrastructure to unlock novel targets to alleviate the burden of other neurological and psychiatric disorders.

Thalamic stimulation induced changes in effective connectivity

Deep brain stimulation (DBS) is a viable treatment for a variety of neurological conditions, however, the mechanisms through which DBS modulates large-scale brain networks are unresolved. Clinical effects of DBS are observed over multiple timescales. In some conditions, such as Parkinson's disease and essential tremor, clinical improvement is observed within seconds. In many other conditions, such as epilepsy, central pain, dystonia, neuropsychiatric conditions or Tourette syndrome, the DBS related effects are believed to require neuroplasticity or reorganization and often take hours to months to observe. To optimize DBS parameters, it is therefore essential to develop electrophysiological biomarkers that characterize whether DBS settings are successfully engaging and modulating the network involved in the disease of interest. In this study, 10 individuals with drug resistant epilepsy undergoing intracranial stereotactic EEG including a thalamus electrode underwent a trial of repetitive thalamic stimulation. We evaluated thalamocortical effective connectivity using single pulse electrical stimulation, both at baseline and following a 145 Hz stimulation treatment trial. We found that when high frequency stimulation was delivered for >1.5 hours, the evoked potentials measured from remote regions were significantly reduced in amplitude and the degree of modulation was proportional to the strength of baseline connectivity. When stimulation was delivered for shorter time periods, results were more variable. These findings suggest that changes in effective connectivity in the network targeted with DBS accumulate over hours of DBS. Stimulation evoked potentials provide an electrophysiological biomarker that allows for efficient data-driven characterization of neuromodulation effects, which could enable new objective approaches for individualized DBS optimization.

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.

Connectivity-based segmentation of the thalamic motor region for deep brain stimulation in essential tremor: A comparison of deterministic and probabilistic tractography

OBJECTIVE

Deep brain stimulation (DBS) studies have shown that stimulation of the motor segment of the thalamus based on probabilistic tractography is predictive of improvement in essential tremor (ET). However, probabilistic methods are computationally demanding, requiring the need for alternative tractography methods for use in the clinical setting. The purpose of this study was to compare probabilistic vs deterministic tractography methods for connectivity-based targeting in patients with ET.

METHODS

Probabilistic and deterministic tractography methods were retrospectively applied to diffusion-weighted data sets in 36 patients with refractory ET. The thalamus and precentral gyrus were selected as regions of interest and fiber tracking was performed between these regions to produce connectivity-based thalamic segmentations, per prior methods. The resultant deterministic target maps were compared with those of thresholded probabilistic maps. The center of gravity (CG) of each connectivity map was determined and the differences in spatial distribution between the tractography methods were characterized. Furthermore, the intersection between the connectivity maps and CGs with the therapeutic volume of tissue activated (VTA) was calculated. A mixed linear model was then used to assess clinical improvement in tremor with volume of overlap.

RESULTS

Both tractography methods delineated the region of the thalamus with connectivity to the precentral gyrus to be within the posterolateral aspect of the thalamus. The average CG of deterministic maps was more medial-posterior in both the left (3.7 ± 1.3 mm3) and the right (3.5 ± 2.2 mm3) hemispheres when compared to 30 %-thresholded probabilistic maps. Mixed linear model showed that the volume of overlap between CGs of deterministic and probabilistic targeting maps and therapeutic VTAs were significant predictors of clinical improvement.

CONCLUSIONS

Deterministic tractography can reconstruct DBS thalamic target maps in approximately 5 min comparable to those produced by probabilistic methods that require > 12 h to generate. Despite differences in CG between the methods, both deterministic-based and probabilistic targeting were predictive of clinical improvement in ET.

Network Localization of State and Trait of Auditory Verbal Hallucinations in Schizophrenia

BACKGROUND AND HYPOTHESIS

Neuroimaging studies investigating the neural substrates of auditory verbal hallucinations (AVH) in schizophrenia have yielded mixed results, which may be reconciled by network localization. We sought to examine whether AVH-state and AVH-trait brain alterations in schizophrenia localize to common or distinct networks.

STUDY DESIGN

We initially identified AVH-state and AVH-trait brain alterations in schizophrenia reported in 48 previous studies. By integrating these affected brain locations with large-scale discovery and validation resting-state functional magnetic resonance imaging datasets, we then leveraged novel functional connectivity network mapping to construct AVH-state and AVH-trait dysfunctional networks.

STUDY RESULTS

The neuroanatomically heterogeneous AVH-state and AVH-trait brain alterations in schizophrenia localized to distinct and specific networks. The AVH-state dysfunctional network comprised a broadly distributed set of brain regions mainly involving the auditory, salience, basal ganglia, language, and sensorimotor networks. Contrastingly, the AVH-trait dysfunctional network manifested as a pattern of circumscribed brain regions principally implicating the caudate and inferior frontal gyrus. Additionally, the AVH-state dysfunctional network aligned with the neuromodulation targets for effective treatment of AVH, indicating possible clinical relevance.

CONCLUSIONS

Apart from unifying the seemingly irreproducible neuroimaging results across prior AVH studies, our findings suggest different neural mechanisms underlying AVH state and trait in schizophrenia from a network perspective and more broadly may inform future neuromodulation treatment for AVH.

Proceedings of the 11th Annual Deep Brain Stimulation Think Tank: pushing the forefront of neuromodulation with functional network mapping, biomarkers for adaptive DBS, bioethical dilemmas, AI-guided neuromodulation, and translational advancements

The Deep Brain Stimulation (DBS) Think Tank XI was held on August 9-11, 2023 in Gainesville, Florida with the theme of "Pushing the Forefront of Neuromodulation". The keynote speaker was Dr. Nico Dosenbach from Washington University in St. Louis, Missouri. He presented his research recently published in Nature inn a collaboration with Dr. Evan Gordon to identify and characterize the somato-cognitive action network (SCAN), which has redefined the motor homunculus and has led to new hypotheses about the integrative networks underpinning therapeutic DBS. The DBS Think Tank was founded in 2012 and provides an open platform where clinicians, engineers, and researchers (from industry and academia) can freely discuss current and emerging DBS technologies, as well as logistical and ethical issues facing the field. The group estimated that globally more than 263,000 DBS devices have been implanted for neurological and neuropsychiatric disorders. This year's meeting was focused on advances in the following areas: cutting-edge translational neuromodulation, cutting-edge physiology, advances in neuromodulation from Europe and Asia, neuroethical dilemmas, artificial intelligence and computational modeling, time scales in DBS for mood disorders, and advances in future neuromodulation devices.

Coupling between beta band and high frequency oscillations as a clinically useful biomarker for DBS

Beta hypersynchrony was recently introduced into clinical practice in Parkinson's disease (PD) to identify the best stimulation contacts and for adaptive deep brain stimulation (aDBS) sensing. However, many other oscillopathies accompany the disease, and beta power sensing may not be optimal for all patients. The aim of this work was to study the potential clinical usefulness of beta power phase-amplitude coupling (PAC) with high frequency oscillations (HFOs). Subthalamic nucleus (STN) local field potentials (LFPs) from externalized DBS electrodes were recorded and analyzed in PD patients (n = 19). Beta power and HFOs were evaluated in a resting-state condition; PAC was then studied and compared with the electrode contact positions, structural connectivity, and medication state. Beta-HFO PAC (mainly in the 200-500 Hz range) was observed in all subjects. PAC was detectable more specifically in the motor part of the STN compared to beta power and HFOs. Moreover, the presence of PAC better corresponds to the stimulation setup based on the clinical effect. PAC is also sensitive to the laterality of symptoms and dopaminergic therapy, where the greater PAC cluster reflects the more affected side and medication "off" state. Coupling between beta power and HFOs is known to be a correlate of the PD "off" state. Beta-HFO PAC seems to be more sensitive than beta power itself and could be more helpful in the selection of the best clinical stimulation contact and probably also as a potential future input signal for aDBS.

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.

Elevating the field for applying neuroimaging to individual patients in psychiatry

Although neuroimaging has been widely applied in psychiatry, much of the exuberance in decades past has been tempered by failed replications and a lack of definitive evidence to support the utility of imaging to inform clinical decisions. There are multiple promising ways forward to demonstrate the relevance of neuroimaging for psychiatry at the individual patient level. Ultra-high field magnetic resonance imaging is developing as a sensitive measure of neurometabolic processes of particular relevance that holds promise as a new way to characterize patient abnormalities as well as variability in response to treatment. Neuroimaging may also be particularly suited to the science of brain stimulation interventions in psychiatry given that imaging can both inform brain targeting as well as measure changes in brain circuit communication as a function of how effectively interventions improve symptoms. We argue that a greater focus on individual patient imaging data will pave the way to stronger relevance to clinical care in psychiatry. We also stress the importance of using imaging in symptom-relevant experimental manipulations and how relevance will be best demonstrated by pairing imaging with differential treatment prediction and outcome measurement. The priorities for using brain imaging to inform psychiatry may be shifting, which compels the field to solidify clinical relevance for individual patients over exploratory associations and biomarkers that ultimately fail to replicate.

Seizing the Brain Networks in Lesional Focal Epilepsies

Mapping Lesion-Related Epilepsy to a Human Brain Network Frederic L.W. V. J. Schaper, Janne Nordberg, Alexander L. Cohen, Christopher Lin, Joey Hsu, Andreas Horn, Michael A. Ferguson, Shan H. Siddiqi,William Drew, Louis Soussand, Anderson M. Winkler, Marta Simó, Jordi Bruna, Sylvain Rheims, Marc Guenot, Marco Bucci, Lauri Nummenmaa, Julie Staals, Albert J. Colon, Linda Ackermans, Ellen J. Bubrick, Jurriaan M. Peters, OnaWu, Natalia S. Rost, Jordan Grafman, Hal Blumenfeld, Yasin Temel, Rob P. W. Rouhl, Juho Joutsa, Michael D. Fox. JAMA Neurol . 2023;80(9):891-902. doi:10.1001/jamaneurol.2023.1988 . PMID: 37399040. PMCID: PMC10318550 Importance: It remains unclear why lesions in some locations cause epilepsy while others do not. Identifying the brain regions or networks associated with epilepsy by mapping these lesions could inform prognosis and guide interventions. Objective: To assess whether lesion locations associated with epilepsy map to specific brain regions and networks. Design, Setting, and Participants: This case-control study used lesion location and lesion network mapping to identify the brain regions and networks associated with epilepsy in a discovery data set of patients with poststroke epilepsy and control patients with stroke. Patients with stroke lesions and epilepsy (n = 76) or no epilepsy (n = 625) were included. Generalizability to other lesion types was assessed using 4 independent cohorts as validation data sets. The total number of patients across all datasets (both discovery and validation datasets) were 347 with epilepsy and 1126 without. Therapeutic relevance was assessed using deep brain stimulation sites that improve seizure control. Data were analyzed from September 2018 through December 2022. All shared patient data were analyzed and included; no patients were excluded. Main Outcomes and Measures: Epilepsy or no epilepsy. Results: Lesion locations from 76 patients with poststroke epilepsy (39 [51%] male; mean [SD] age, 61.0 [14.6] years; mean [SD] follow-up, 6.7 [2.0] years) and 625 control patients with stroke (366 [59%] male; mean [SD] age, 62.0 [14.1] years; follow-up range, 3-12 months) were included in the discovery data set. Lesions associated with epilepsy occurred in multiple heterogenous locations spanning different lobes and vascular territories. However, these same lesion locations were part of a specific brain network defined by functional connectivity to the basal ganglia and cerebellum. Findings were validated in 4 independent cohorts including 772 patients with brain lesions (271 [35%] with epilepsy; 515 [67%] male; median [IQR] age, 60 [50-70] years; follow-up range, 3-35 years). Lesion connectivity to this brain network was associated with increased risk of epilepsy after stroke (odds ratio [OR], 2.82; 95%CI, 2.02-4.10; P < .001) and across different lesion types (OR, 2.85; 95%CI, 2.23-3.69; P < .001). Deep brain stimulation site connectivity to this same network was associated with improved seizure control (r , 0.63; P < .001) in 30 patients with drug-resistant epilepsy (21 [70%] male; median [IQR] age, 39 [32-46] years; median [IQR] follow-up, 24 [16-30] months). Conclusions and Relevance: The findings in this study indicate that lesion-related epilepsy mapped to a human brain network, which could help identify patients at risk of epilepsy after a brain lesion and guide brain stimulation therapies.

The future of brain circuit-targeted therapeutics

The principle of targeting brain circuits has drawn increasing attention with the growth of brain stimulation treatments such as transcranial magnetic stimulation (TMS), deep brain stimulation (DBS), and focused ultrasound (FUS). Each of these techniques can effectively treat different neuropsychiatric disorders, but treating any given disorder depends on choosing the right treatment target. Here, we propose a three-phase framework for identifying and modulating these targets. There are multiple approaches to identifying a target, including correlative neuroimaging, retrospective optimization based on existing stimulation sites, and lesion localization. These techniques can then be optimized using personalized neuroimaging, physiological monitoring, and engagement of a specific brain state using pharmacological or psychological interventions. Finally, a specific stimulation modality or combination of modalities can be chosen after considering the advantages and tradeoffs of each. While there is preliminary literature to support different components of this framework, there are still many unanswered questions. This presents an opportunity for the future growth of research and clinical care in brain circuit therapeutics.

Causal Discovery for fMRI data: Challenges, Solutions, and a Case Study

Designing studies that apply causal discovery requires navigating many researcher degrees of freedom. This complexity is exacerbated when the study involves fMRI data. In this paper we (i) describe nine challenges that occur when applying causal discovery to fMRI data, (ii) discuss the space of decisions that need to be made, (iii) review how a recent case study made those decisions, (iv) and identify existing gaps that could potentially be solved by the development of new methods. Overall, causal discovery is a promising approach for analyzing fMRI data, and multiple successful applications have indicated that it is superior to traditional fMRI functional connectivity methods, but current causal discovery methods for fMRI leave room for improvement.

Anatomical substrates and connectivity for bradykinesia motor features in Parkinson's disease after subthalamic nucleus deep brain stimulation

Parkinsonian bradykinesia is rated using a composite scale incorporating the slowed frequency of repetitive movements, decrement amplitude and arrhythmicity. Differential localization of these movement components within the basal ganglia will drive the development of more personalized network-targeted symptomatic therapies. In this study, using an optical motion sensor, we evaluated the amplitude and frequency of hand movements during a grasping task with subthalamic nucleus deep brain stimulation 'on' or 'off' in 15 patients with Parkinson's disease. The severity of bradykinesia was assessed blindly using the Unified Parkinson's Disease Rating Part III scale. The volumes of activated tissue of each subject were estimated where changes in amplitude and frequency were mapped to identify distinct anatomical substrates of each component in the subthalamic nucleus. The volumes of activated tissue were used to seed a normative functional connectome to generate connectivity maps associated with amplitude and frequency changes. Deep brain stimulation-induced change in amplitude was negatively correlated with a change in Unified Parkinson's Disease Rating Part III scale for right (r = -0.65, P < 0.05) and left hand grasping scores (r = -0.63, P < 0.05). The change in frequency was negatively correlated with amplitude for both right (r = -0.63, P < 0.05) and left hands (r = -0.57, P < 0.05). The amplitude and frequency changes were represented as a spatial gradient with overlapping and non-overlapping regions spanning the anteromedial-posterolateral axis of the subthalamic nucleus. Whole-brain correlation maps between functional connectivity and motor changes were also inverted between amplitude and frequency changes. Deep brain stimulation-associated changes in frequency and amplitude were topographically and distinctly represented both locally in the subthalamic nucleus and in whole-brain functional connectivity.

The Related Factors and Effect of Electrode Displacement on Motor Outcome of Subthalamic Nuclei Deep Brain Stimulation in Parkinson's Disease

BACKGROUND

Previous studies have revealed the existence of electrode displacement during subthalamic nucleus deep brain stimulation (STN-DBS). However, the effect of electrode displacement on treatment outcomes is still unclear. In this study, we aimed to analyze the related factors of electrode displacement and assess postoperative electrode displacement in relation to the motor outcomes of STN-DBS.

METHODS

A total of 88 patients aged 62.73 ± 6.35 years (55 males and 33 females) with Parkinson's disease undergoing STN-DBS, with comprehensive clinical characterization before and 1 month after surgery, were involved retrospectively and divided into a cross-incision group and cannula puncture group according to different dura opening methods. The electrode displacement, unilateral pneumocephalus volume percent (uPVP), and brain volume percent were estimated.

RESULTS

A significant anterior and lateral electrode displacement was observed among all implanted electrodes after pneumocephalus absorption (p < 0.0001). The degree of electrode displacement was positively correlated with the uPVP (p = 0.005) and smaller in females than males (p = 0.0384). Electrode displacement was negatively correlated with motor improvement following STN-DBS in both on-medication and off-medication conditions (p < 0.05). Dural puncture reduced the uPVP (p < 0.0001) and postoperative electrode displacement (p = 0.0086) compared with dural incision.

CONCLUSIONS

Electrode displacement had a negative impact on the therapeutic efficacy of STN-DBS. Opening the dura via cannula puncture is recommended to increase the accuracy of the lead implantation.

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.

Multiplexity of human brain oscillations as a personal brain signature

Human individuality is likely underpinned by the constitution of functional brain networks that ensure consistency of each person's cognitive and behavioral profile. These functional networks should, in principle, be detectable by noninvasive neurophysiology. We use a method that enables the detection of dominant frequencies of the interaction between every pair of brain areas at every temporal segment of the recording period, the dominant coupling modes (DoCM). We apply this method to brain oscillations, measured with magnetoencephalography (MEG) at rest in two independent datasets, and show that the spatiotemporal evolution of DoCMs constitutes an individualized brain fingerprint. Based on this successful fingerprinting we suggest that DoCMs are important targets for the investigation of neural correlates of individual psychological parameters and can provide mechanistic insight into the underlying neurophysiological processes, as well as their disturbance in brain diseases.

Mediation of Tremor Control by the Decussating and Nondecussating Part of the Dentato-Rubro-Thalamic Tract in Deep Brain Stimulation in Essential Tremor: Which Part Should Be Stimulated?

OBJECTIVES

The dentato-rubro-thalamic tract (DRTT) has been found to play a major role in the mechanisms of tremor alleviation by deep brain stimulation (DBS) in essential tremor (ET). Still, the influence of the two different parts of the DRTT, consisting of crossing and nondecussating fibers, is not yet clear with respect to tremor reduction. The aim of this study was to assess the influence of the crossing and the nondecussating part of the DRTT on tremor control in ET.

MATERIALS AND METHODS

We investigated 80 electrode contacts in ten patients with ET who received bilateral DBS of the Nucleus ventralis intermedius of the thalamus (VIM). Preoperatively and with patients under general anesthesia, 3T magnetic resonance imaging scans were performed, including Diffusion Tensor Imaging scans with 64 gradient directions. We calculated the course of the two parts of the DRTT based on a workflow for probabilistic fiber tracking including protocols for correction of susceptibility- and eddy current-induced distortions. Distances of electrode contacts were correlated with clinical data from neurologic single pole testing.

RESULTS

Voltage- and current-steered systems were analyzed separately. Regarding postural tremor, effective contacts showed significantly lower distances to both parts of the DRTT (crossing p < 0.001, nondecussating p < 0.05) in voltage-steered systems. Regarding intentional tremor, significant results were only found for the crossing part (p < 0.01). Regarding both tremor types, effective contacts were closer to the crossing part, unlike less effective contacts. Nonlinear regression analyses using a logistic model showed higher coefficients for the crossing part of the DRTT. Multivariate regression models including distances to both parts of the DRTT showed a significant influence of only the crossing part. Analysis of current-steered systems showed unstable data, probably because of the small number of analyzed patients.

CONCLUSIONS

Our data suggest an involvement of both parts of the DRTT in tremor reduction, indicating mediation of DBS effects by both fiber bundles, although the crossing part showed stronger correlations with good clinical responses. Nevertheless, special attention should be paid to methodologic aspects when using probabilistic tractography for patient-specific targeting to avoid uncertain and inaccurate results.

Dorsal subthalamic nucleus targeting in deep brain stimulation: microelectrode recording versus 7-Tesla connectivity

Connectivity-derived 7-Tesla MRI segmentation and intraoperative microelectrode recording can both assist subthalamic nucleus targeting for deep brain stimulation in Parkinson's disease. It remains unclear whether deep brain stimulation electrodes placed in the 7-Tesla MRI segmented subdivision with predominant projections to cortical motor areas (hyperdirect pathway) achieve superior motor improvement and whether microelectrode recording can accurately distinguish the motor subdivision. In 25 patients with Parkinson's disease, deep brain stimulation electrodes were evaluated for being inside or outside the predominantly motor-connected subthalamic nucleus (motor-connected subthalamic nucleus or non-motor-connected subthalamic nucleus, respectively) based on 7-Tesla MRI connectivity segmentation. Hemi-body motor improvement (Movement Disorder Society Unified Parkinson's Disease Rating Scale, Part III) and microelectrode recording characteristics of multi- and single-unit activities were compared between groups. Deep brain stimulation electrodes placed in the motor-connected subthalamic nucleus resulted in higher hemi-body motor improvement, compared with electrodes placed in the non-motor-connected subthalamic nucleus (80% versus 52%, P < 0.0001). Multi-unit activity was found slightly higher in the motor-connected subthalamic nucleus versus the non-motor-connected subthalamic nucleus (P < 0.001, receiver operating characteristic 0.63); single-unit activity did not differ between groups. Deep brain stimulation in the connectivity-derived 7-Tesla MRI subthalamic nucleus motor segment produced a superior clinical outcome; however, microelectrode recording did not accurately distinguish this subdivision within the subthalamic nucleus.

Advances in Deep Brain Stimulation: From Mechanisms to Applications

Deep brain stimulation (DBS) is an effective therapy for various neurologic and neuropsychiatric disorders, involving chronic implantation of electrodes into target brain regions for electrical stimulation delivery. Despite its safety and efficacy, DBS remains an underutilized therapy. Advances in the field of DBS, including in technology, mechanistic understanding, and applications have the potential to expand access and use of DBS, while also improving clinical outcomes. Developments in DBS technology, such as MRI compatibility and bidirectional DBS systems capable of sensing neural activity while providing therapeutic stimulation, have enabled advances in our understanding of DBS mechanisms and its application. In this review, we summarize recent work exploring DBS modulation of target networks. We also cover current work focusing on improved programming and the development of novel stimulation paradigms that go beyond current standards of DBS, many of which are enabled by sensing-enabled DBS systems and have the potential to expand access to DBS.

Neurophysiological mechanisms of deep brain stimulation across spatiotemporal resolutions

Deep brain stimulation is a neuromodulatory treatment for managing the symptoms of Parkinson's disease and other neurological and psychiatric disorders. Electrodes are chronically implanted in disease-relevant brain regions and pulsatile electrical stimulation delivery is intended to restore neurocircuit function. However, the widespread interest in the application and expansion of this clinical therapy has preceded an overarching understanding of the neurocircuit alterations invoked by deep brain stimulation. Over the years, various forms of neurophysiological evidence have emerged which demonstrate changes to brain activity across spatiotemporal resolutions; from single neuron, to local field potential, to brain-wide cortical network effects. Though fruitful, such studies have often led to debate about a singular putative mechanism. In this Update we aim to produce an integrative account of complementary instead of mutually exclusive neurophysiological effects to derive a generalizable concept of the mechanisms of deep brain stimulation. In particular, we offer a critical review of the most common historical competing theories, an updated discussion on recent literature from animal and human neurophysiological studies, and a synthesis of synaptic and network effects of deep brain stimulation across scales of observation, including micro-, meso- and macroscale circuit alterations.