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

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

Ipsilateral and axial tremor response to focused ultrasound thalamotomy for essential tremor: clinical outcomes and probabilistic mapping.

BACKGROUND: MR-guided focused ultrasound (MRgFUS) thalamotomy has been shown to be a safe and effective treatment for essential tremor (ET). OBJECTIVE: To investigate the effects of MRgFUS in patients with ET with an emphasis on ipsilateral-hand and axial tremor subscores. METHODS: Tremor scores and adverse effects of 100 patients treated between 2012 and 2018 were assessed at 1 week, 3, 12, and 24 months. A subgroup analysis of ipsilateral-hand tremor responders (defined as patients with ≥30% improvement at any time point) and non-responders was performed. Correlations and predictive factors for improvement were analysed. Weighted probabilistic maps of improvement were generated. RESULTS: Significant improvement in axial, contralateral-hand and total tremor scores was observed at all study visits from baseline (p<0.0001). There was no significant improvement in ipsilateral subscores. A subset of patients (n=20) exhibited group-level ipsilateral-hand improvement that remained significant through all follow-ups (p<0.001). Multivariate regression analysis revealed that higher baseline scores predict better improvement in ipsilateral-hand and axial tremor. Probabilistic maps demonstrated that the lesion hotspot for axial improvement was situated more medially than that for contralateral improvement. CONCLUSION: MRgFUS significantly improved axial, contralateral-hand and total tremor scores. In a subset of patients, a consistent group-level treatment effect was observed for ipsilateral-hand tremor. While ipsilateral improvement seemed to be less directly related to lesion location, a spatial relationship between lesion location and axial and contralateral improvement was observed that proved consistent with the somatotopic organisation of the ventral intermediate nucleus. TRIAL REGISTRATION NUMBERS: NCT01932463, NCT01827904, and NCT02252380.

Use of Functional Magnetic Resonance Imaging to Assess How Motor Phenotypes of Parkinson's Disease Respond to Deep Brain Stimulation.

BACKGROUND: Deep brain stimulation (DBS) is a well-accepted treatment of Parkinson's disease (PD). Motor phenotypes include tremor-dominant (TD), akinesia-rigidity (AR), and postural instability gait disorder (PIGD). The mechanism of action in how DBS modulates motor symptom relief remains unknown. OBJECTIVE: Blood oxygen level-dependent (BOLD) functional magnetic resonance imaging (fMRI) was used to determine whether the functional activity varies in response to DBS depending on PD phenotypes. MATERIALS AND METHODS: Subjects underwent an fMRI scan with DBS cycling ON and OFF. The effects of DBS cycling on BOLD activation in each phenotype were documented through voxel-wise analysis. For each region of interest, ANOVAs were performed using T-values and covariate analyses were conducted. Further, a correlation analysis was performed comparing stimulation settings to T-values. Lastly, T-values of subjects with motor improvement were compared to those who worsened. RESULTS: As a group, BOLD activation with DBS-ON resulted in activation in the motor thalamus (p < 0.01) and globus pallidus externa (p < 0.01). AR patients had more activation in the supplementary motor area (SMA) compared to PIGD (p < 0.01) and TD cohorts (p < 0.01). Further, the AR cohort had more activation in primary motor cortex (MI) compared to the TD cohort (p = 0.02). Implanted nuclei (p = 0.01) and phenotype (p = <0.01) affected activity in MI and phenotype alone affected SMA activity (p = <0.01). A positive correlation was seen between thalamic activation and pulse-width (p = 0.03) and between caudate and total electrical energy delivered (p = 0.04). CONCLUSIONS: These data suggest that DBS modulates network activity differently based on patient motor phenotype. Improved understanding of these differences may further our knowledge about the mechanisms of DBS action on PD motor symptoms and to optimize treatment.

Disruption of functional organization within the primary motor cortex in children with autism.

Accumulating evidence suggests that motor impairments are prevalent in autism spectrum disorder (ASD), relate to the social and communicative deficits at the core of the diagnosis and may reflect abnormal connectivity within brain networks underlying motor control and learning. Parcellation of resting-state functional connectivity data using spectral clustering approaches has been shown to be an effective means of visualizing functional organization within the brain but has most commonly been applied to explorations of normal brain function. This article presents a parcellation of a key area of the motor network, the primary motor cortex (M1), a key area of the motor control network, in adults, typically developing (TD) children and children with ASD and introduces methods for selecting the number of parcels, matching parcels across groups and testing group differences. The parcellation is based solely on patterns of connectivity between individual M1 voxels and all voxels outside of M1, and within all groups, a gross dorsomedial to ventrolateral organization emerged within M1 which was left-right symmetric. Although this gross organizational scheme was present in both groups of children, statistically significant group differences in the size and segregation of M1 parcels within regions of the motor homunculus corresponding to the upper and lower limbs were observed. Qualitative comparison of the M1 parcellation for children with ASD with that of younger and older TD children suggests that these organizational differences, with a lack of differentiation between lower limb/trunk regions and upper limb/hand regions, may be due, at least in part, to a delay in functional specialization within the motor cortex.

Optogenetic-guided cortical plasticity after nerve injury.

Peripheral nerve injury causes sensory dysfunctions that are thought to be attributable to changes in neuronal activity occurring in somatosensory cortices both contralateral and ipsilateral to the injury. Recent studies suggest that distorted functional response observed in deprived primary somatosensory cortex (S1) may be the result of an increase in inhibitory interneuron activity and is mediated by the transcallosal pathway. The goal of this study was to develop a strategy to manipulate and control the transcallosal activity to facilitate appropriate plasticity by guiding the cortical reorganization in a rat model of sensory deprivation. Since transcallosal fibers originate mainly from excitatory pyramidal neurons somata situated in laminae III and V, the excitatory neurons in rat S1 were engineered to express halorhodopsin, a light-sensitive chloride pump that triggers neuronal hyperpolarization. Results from electrophysiology, optical imaging, and functional MRI measurements are concordant with that within the deprived S1, activity in response to intact forepaw electrical stimulation was significantly increased by concurrent illumination of halorhodopsin over the healthy S1. Optogenetic manipulations effectively decreased the adverse inhibition of deprived cortex and revealed the major contribution of the transcallosal projections, showing interhemispheric neuroplasticity and thus, setting a foundation to develop improved rehabilitation strategies to restore cortical functions.

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.

Motor "dexterity"?: Evidence that left hemisphere lateralization of motor circuit connectivity is associated with better motor performance in children.

Motor control relies on well-established motor circuits, which are critical for typical child development. Although many imaging studies have examined task activation during motor performance, none have examined the relationship between functional intrinsic connectivity and motor ability. The current study investigated the relationship between resting state functional connectivity within the motor network and motor performance assessment outside of the scanner in 40 typically developing right-handed children. Better motor performance correlated with greater left-lateralized (mean left hemisphere-mean right hemisphere) motor circuit connectivity. Speed, rhythmicity, and control of movements were associated with connectivity within different individual region pairs: faster speed was associated with more left-lateralized putamen-thalamus connectivity, less overflow with more left-lateralized supplementary motor-primary motor connectivity, and less dysrhythmia with more left-lateralized supplementary motor-anterior cerebellar connectivity. These findings suggest that for right-handed children, superior motor development depends on the establishment of left-hemisphere dominance in intrinsic motor network connectivity.

Tactile, gustatory, and visual biofeedback stimuli modulate neural substrates of deglutition.

It has been well established that swallowing kinematics are modified with different forms of exogenous and endogenous input, however the underlying neural substrates associated with these effects are largely unknown. Our objective was to determine whether the swallowing BOLD response is modulated with heightened sensory modalities (taste, cutaneous electrical stimulation, and visual biofeedback) compared to water ingestion (control) in healthy adults across the age span. Habituation and sensitization were also examined for each sensory condition. Our principal findings are that each sensory swallowing condition activated components of the swallowing cortical network, plus regions associated with the particular sensory modality (i.e. primarily frontal motor planning and integration areas with visual condition). Overall, the insula was most commonly active among the sensory modalities. We also discuss gradual increases and decreases in BOLD signal with repeated exposures for each condition. We conclude that both stimulus- and intention-based inputs have unique cortical swallowing networks relative to their modality. This scientific contribution advances our understanding of the mechanisms of normal swallowing cortical control and has the potential to impact clinical uses of these modalities in treatments for neurogenic dysphagia.

Atlas-based analysis of resting-state functional connectivity: evaluation for reproducibility and multi-modal anatomy-function correlation studies.

Resting state functional connectivity MRI (rsfc-MRI) reveals a wealth of information about the functional organization of the brain, but poses unique challenges for quantitative image analysis, mostly related to the large number of voxels with low signal-to-noise ratios. In this study, we tested the idea of using a prior spatial parcellation of the entire brain into various structural units, to perform an analysis on a structure-by-structure, rather than voxel-by-voxel, basis. This analysis, based upon atlas parcels, potentially offers enhanced SNR and reproducibility, and can be used as a common anatomical framework for cross-modality and cross-subject quantitative analysis. We used Large Deformation Diffeomorphic Metric Mapping (LDDMM) and a deformable brain atlas to parcel each brain into 185 regions. To investigate the precision of the cross-subject analysis, we computed inter-parcel correlations in 20 participants, each of whom was scanned twice, as well as the consistency of the connectivity patterns inter- and intra-subject, and the intersession reproducibility. We report significant inter-parcel correlations consistent with previous findings, and high test-retest reliability, an important consideration when the goal is to compare clinical populations. As an example of the cross-modality analysis, correlation with anatomical connectivity is also examined.

CEST phase mapping using a length and offset varied saturation (LOVARS) scheme.

Chemical exchange saturation transfer MRI is a promising new technique for cellular and molecular imaging. This contrast allows the detection of tumors and ischemia without the use of gadolinium as well as the design of microenvironment-sensitive probes that can be discriminated based on their exchange contrast properties and saturation frequency. Current acquisition schemes to detect and analyze this contrast suffer from sensitivity to spatial B0 inhomogeneity and low contrast-to-noise-ratio, which is an obstacle to widespread adoption of the technology. A new method to detect chemical exchange saturation transfer contrast is proposed here, termed "length and offset varied saturation" which acquires a set of images with the saturation parameters varied so as to modulate the exchange contrast. Either fast fourier transform or the general linear model can be employed to decompose the modulation patterns into separate sources of water signal loss. After transformation, a length and offset varied saturation phase map is generated, which is insensitive to B0 inhomogeneity. When collected on live mice bearing 9L gliosarcomas, and compared to the conventional asymmetry in the magnetization transfer ratio map using offset increment correction, the results show that length and offset varied saturation phase mapping obtains about three to four times contrast-to-noise-ratio and exhibits less B0 artifacts.

Dysgeusia induced and resolved by focused ultrasound thalamotomy: case report.

Dysgeusia, or distorted taste, has recently been acknowledged as a complication of thalamic ablation or thalamic deep brain stimulation as a treatment of tremor. In a unique patient, left-sided MR-guided focused ultrasound thalamotomy improved right-sided essential tremor but also induced severe dysgeusia. Although dysgeusia persisted and caused substantial weight loss, tremor slowly relapsed. Therefore, 19 months after the first procedure, the patient underwent a second focused ultrasound thalamotomy procedure, which again improved tremor but also completely resolved the dysgeusia. On the basis of normative and patient-specific whole-brain tractography, the authors determined the relationship between the thalamotomy lesions and the medial border of the medial lemniscus-a surrogate for the solitariothalamic gustatory fibers-after the first and second focused ultrasound thalamotomy procedures. Both tractography methods suggested partial and complete disruption of the solitariothalamic gustatory fibers after the first and second thalamotomy procedures, respectively. The tractography findings in this unique patient demonstrate that incomplete and complete disruption of a neural pathway can induce and resolve symptoms, respectively, and serve as the rationale for ablative procedures for neurological and psychiatric disorders.

Multi-parametric neuroimaging reproducibility: a 3-T resource study.

Modern MRI image processing methods have yielded quantitative, morphometric, functional, and structural assessments of the human brain. These analyses typically exploit carefully optimized protocols for specific imaging targets. Algorithm investigators have several excellent public data resources to use to test, develop, and optimize their methods. Recently, there has been an increasing focus on combining MRI protocols in multi-parametric studies. Notably, these have included innovative approaches for fusing connectivity inferences with functional and/or anatomical characterizations. Yet, validation of the reproducibility of these interesting and novel methods has been severely hampered by the limited availability of appropriate multi-parametric data. We present an imaging protocol optimized to include state-of-the-art assessment of brain function, structure, micro-architecture, and quantitative parameters within a clinically feasible 60-min protocol on a 3-T MRI scanner. We present scan-rescan reproducibility of these imaging contrasts based on 21 healthy volunteers (11 M/10 F, 22-61 years old). The cortical gray matter, cortical white matter, ventricular cerebrospinal fluid, thalamus, putamen, caudate, cerebellar gray matter, cerebellar white matter, and brainstem were identified with mean volume-wise reproducibility of 3.5%. We tabulate the mean intensity, variability, and reproducibility of each contrast in a region of interest approach, which is essential for prospective study planning and retrospective power analysis considerations. Anatomy was highly consistent on structural acquisition (~1-5% variability), while variation on diffusion and several other quantitative scans was higher (~<10%). Some sequences are particularly variable in specific structures (ASL exhibited variation of 28% in the cerebral white matter) or in thin structures (quantitative T2 varied by up to 73% in the caudate) due, in large part, to variability in automated ROI placement. The richness of the joint distribution of intensities across imaging methods can be best assessed within the context of a particular analysis approach as opposed to a summary table. As such, all imaging data and analysis routines have been made publicly and freely available. This effort provides the neuroimaging community with a resource for optimization of algorithms that exploit the diversity of modern MRI modalities. Additionally, it establishes a baseline for continuing development and optimization of multi-parametric imaging protocols.

On the relationship between seed-based and ICA-based measures of functional connectivity.

Brain functional connectivity (FC) refers to inter-regional synchrony of low frequency fluctuations in blood oxygenation level dependent functional magnetic resonance imaging. FC has been evaluated both during task performance and in the "resting" state, yielding reports of FC differences correlated with behavior and diagnosis. Two methodologies are widely used for evaluating FC from blood oxygenation level dependent functional magnetic resonance imaging data: Temporal correlation with a specified seed voxel or small region of interest; and spatial independent component analysis. While results from seed-based and independent component analysis methodologies are generally similar, they are conceptually different. This study is intended to elucidate and illustrate, qualitatively and quantitatively, the relationship between seed and independent component analysis derived measures of FC. Seed-based FC measures are shown to be the sum of independent component analysis-derived within network connectivities and between network connectivities. We present a simple simulation and an experiment on visuomotor activity that highlight this relationship between the two methods.

Variability in post-error behavioral adjustment is associated with functional abnormalities in the temporal cortex in children with ADHD.

BACKGROUND: Error processing is reflected, behaviorally, by slower reaction times (RT) on trials immediately following an error (post-error). Children with attention-deficit hyperactivity disorder (ADHD) fail to show RT slowing and demonstrate increased intra-subject variability (ISV) on post-error trials. The neural correlates of these behavioral deficits remain unclear. The dorsal anterior cingulate cortex (ACC) and lateral prefrontal cortex (PFC) are key regions implicated in error processing and subsequent behavioral adjustment. We hypothesized that children with ADHD, compared to typically developing (TD) controls, would exhibit reduced PFC activation during post-error (versus post-correct inhibition) trials and reduced dACC activation during error (versus correct inhibition) trials. METHODS: Using functional Magnetic Resonance Imaging (fMRI) and a Go/No-Go task, we analyzed the neural correlates of error processing in 13 children with ADHD and 17 TD children. RESULTS: Behaviorally, children with ADHD showed similar RT slowing but increased ISV compared to controls. The post-error contrast revealed a relative increase in blood-oxygen-level dependent (BOLD) signal in the middle/inferior temporal cortex (TempC), the ACC/supplementary motor area (SMA) and the somatosensory/auditory cortex (AudC) in children with ADHD compared to controls. Importantly, in the ADHD group, increased post-error temporal cortex activity was associated with lower ISV. During error (versus correct inhibition) trials, no between-group differences were detected. However, in children with ADHD lower ISV was associated with decreased insula and increased precentral gyrus activity. CONCLUSIONS: In children with ADHD, post-error neural activity suggests, first, a shift of attention towards task-irrelevant stimuli (AudC), and second, a recruitment of compensatory regions that resolve stimulus conflict (TempC) and improve response selection/execution (ACC/SMA). ADHD children with higher temporal cortex activation showed lower ISV, suggesting that functional abnormalities in the compensatory temporal regions contribute to increased variability. Moreover, increased ISV may be related to an over-sensitivity to negative outcomes during error trials in ADHD (insula correlation).

Use of Functional MRI to Assess Effects of Deep Brain Stimulation Frequency Changes on Brain Activation in Parkinson Disease.

BACKGROUND: Models have been developed for predicting ideal contact and amplitude for subthalamic nucleus (STN) deep brain stimulation (DBS) for Parkinson disease (PD). Pulse-width is generally varied to modulate the size of the energy field produced. Effects of varying frequency in humans have not been systematically evaluated. OBJECTIVE: To examine how altered frequencies affect blood oxygen level-dependent activation in PD. METHODS: PD subjects with optimized DBS programming underwent functional magnetic resonance imaging (fMRI). Frequency was altered and fMRI scans/Unified Parkinson Disease Rating Scale motor subunit (UPDRS-III) scores were obtained. Analysis using DBS-OFF data was used to determine which regions were activated during DBS-ON. Peak activity utilizing T-values was obtained and compared. RESULTS: At clinically optimized settings (n = 14 subjects), thalamic, globus pallidum externa (GPe), and posterior cerebellum activation were present. Activation levels significantly decreased in the thalamus, anterior cerebellum, and the GPe when frequency was decreased (P < .001). Primary somatosensory cortex activation levels significantly decreased when frequency was increased by 30 Hz, but not 60 Hz. Sex, age, disease/DBS duration, and bilaterality did not significantly affect the data. Retrospective analysis of fMRI activation patterns predicted optimal frequency in 11/14 subjects. CONCLUSION: We show the first data with fMRI of STN DBS-ON while synchronizing cycling with magnetic resonance scanning. At clinically optimized settings, an fMRI signature of thalamic, GPe, and posterior cerebellum activation was seen. Reducing frequency significantly decreased thalamic, GPe, and anterior cerebellum activation. Current standard-of-care programming can take up to 6 mo using UPDRS-III testing alone. We provide preliminary evidence that using fMRI signature of frequency may have clinical utility and feasibility.

Predicting optimal deep brain stimulation parameters for Parkinson's disease using functional MRI and machine learning.

Commonly used for Parkinson's disease (PD), deep brain stimulation (DBS) produces marked clinical benefits when optimized. However, assessing the large number of possible stimulation settings (i.e., programming) requires numerous clinic visits. Here, we examine whether functional magnetic resonance imaging (fMRI) can be used to predict optimal stimulation settings for individual patients. We analyze 3 T fMRI data prospectively acquired as part of an observational trial in 67 PD patients using optimal and non-optimal stimulation settings. Clinically optimal stimulation produces a characteristic fMRI brain response pattern marked by preferential engagement of the motor circuit. Then, we build a machine learning model predicting optimal vs. non-optimal settings using the fMRI patterns of 39 PD patients with a priori clinically optimized DBS (88% accuracy). The model predicts optimal stimulation settings in unseen datasets: a priori clinically optimized and stimulation-naïve PD patients. We propose that fMRI brain responses to DBS stimulation in PD patients could represent an objective biomarker of clinical response. Upon further validation with additional studies, these findings may open the door to functional imaging-assisted DBS programming.

Two-stage decompositions for the analysis of functional connectivity for fMRI with application to Alzheimer's disease risk.

Functional connectivity is the study of correlations in measured neurophysiological signals. Altered functional connectivity has been shown to be associated with a variety of cognitive and memory impairments and dysfunction, including Alzheimer's disease. In this manuscript we use a two-stage application of the singular value decomposition to obtain data driven population-level measures of functional connectivity in functional magnetic resonance imaging (fMRI). The method is computationally simple and amenable to high dimensional fMRI data with large numbers of subjects. Simulation studies suggest the ability of the decomposition methods to recover population brain networks and their associated loadings. We further demonstrate the utility of these decompositions in a functional logistic regression model. The method is applied to a novel fMRI study of Alzheimer's disease risk under a verbal paired associates task. We found an indication of alternative connectivity in clinically asymptomatic at-risk subjects when compared to controls, which was not significant in the light of multiple comparisons adjustment. The relevant brain network loads primarily on the temporal lobe and overlaps significantly with the olfactory areas and temporal poles.

Mapping the network underpinnings of central poststroke pain and analgesic neuromodulation.

Central poststroke pain (CPSP) is a debilitating and often treatment-refractory condition that affects numerous stroke patients. The location of lesions most likely to cause pain and the identity of the functional brain networks that they impinge upon remain incompletely understood. We aimed to (1) elucidate which lesion locations are most frequently accompanied by pain; (2) explore CPSP-associated functional networks; and (3) examine how neuromodulation interacts with these networks. This multisite study investigated 17 CPSP patients who received deep brain stimulation (DBS; n = 12) or motor cortex stimulation (MCS; n = 5). Pain-causing lesions were manually segmented and normalized to standard space. To identify areas linked to high risk of pain, the locations of CPSP lesions and 220 control lesions were compared using voxelwise odds ratio mapping. The functional connectivity of pain-causing lesions was obtained using a large (n = 1000) normative resting-state functional MRI connectome and compared to that of control lesions and therapeutic DBS activation volumes. Brain regions most associated with CPSP risk (highest value = 63 times) were located along the ascending somatosensory pathways. These areas and the majority of individual CPSP lesions were functionally connected to anterior/middle cingulate cortex, insula, thalamus, and inferior parietal lobule (PBonferroni < 0.05). The extent of connectivity to the thalamus, inferior parietal lobule, and precuneus also differed between CPSP and control lesions (PBonferroni < 0.05). Posterior insula and thalamus shared connectivity with both CPSP lesions and pain-alleviating DBS activation volumes (PBonferroni < 0.05). These findings further clarify the topography and functional connectivity of pain-causing brain lesions, and provide new insights into the network-level mechanism of CPSP neuromodulation.

Probing the circuitry of panic with deep brain stimulation: Connectomic analysis and review of the literature.

BACKGROUND: Panic attacks affect a sizeable proportion of the population. The neurocircuitry of panic remains incompletely understood. OBJECTIVE: To investigate the neuroanatomical underpinnings of panic attacks induced by deep brain stimulation (DBS) through (1) connectomic analysis of an obsessive-compulsive disorder patient who experienced panic attacks during inferior thalamic peduncle DBS; (2) appraisal of existing clinical reports on DBS-induced panic attacks. METHODS: Panicogenic, ventral contact stimulation was compared with benign stimulation at other contacts using volume of tissue activated (VTA) modelling. Networks associated with the panicogenic zone were investigated using state-of-the-art normative connectivity mapping. In addition, a literature search for prior reports of DBS-induced panic attacks was conducted. RESULTS: Panicogenic VTAs impinged primarily on the tuberal hypothalamus. Compared to non-panicogenic VTAs, panicogenic loci were significantly functionally coupled to limbic and brainstem structures, including periaqueductal grey and amygdala. Previous studies found stimulation of these areas can also provoke panic attacks. CONCLUSIONS: DBS in the region of the tuberal hypothalamus elicited panic attacks in a single obsessive-compulsive disorder patient and recruited a network of structures previously implicated in panic pathophysiology, reinforcing the importance of the hypothalamus as a hub of panicogenic circuitry.

Author Correction: Noninvasive sub-organ ultrasound stimulation for targeted neuromodulation.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.