Mapping dysfunctional circuits in the frontal cortex using deep brain stimulation

Precisely-timed outpatient recordings of subcortical local field potentials from wireless streaming-capable deep-brain stimulators: a method and toolbox

BACKGROUND

Investigations of the electrophysiological mechanisms of the human subcortex have relied on recording local field potentials (LFPs) during deep-brain stimulation (DBS) neurosurgery. However, the neurosurgical setting severely restricts the research use of these recordings. Recently developed sensing-capable DBS devices wirelessly stream subcortical LFPs in outpatient settings. These recordings have tremendous potential for research. However, synchronizing them with other behavior or neural recordings is challenging, as the clinical devices do not accept digital timing information.

NEW METHOD

Switching the DBS device on introduces transient yet consistent artifacts in both the LFP and simultaneous scalp-EEG recordings. We use these artifacts as a reference to align these recordings (N = 20). We tested whether the alignment was precise enough to match a ground truth state (large artifacts produced by transcranial magnetic stimulation, TMS), yielded trial-averaged event-locked LFPs, and phase consistency across trials. We further evaluated the consistency of task-related LFPs across outpatient and perisurgical recordings.

RESULTS AND COMPARISON WITH EXISTING METHOD(S)

Previous alignment methods were limited because they relied on inconsistent on/offset features of DBS artifacts caused by ongoing stimulation. Moreover, they only provided limited validation. Our highly precise alignment method showed a maximum deviation of only 8 ms - clearly superior to prior techniques. Furthermore, event-related activity patterns were comparable across outpatient and perisurgical LFP recordings.

CONCLUSIONS

We present a method and a MATLAB toolbox that inserts the most precise digital timing information into wirelessly-streamed DBS-LFP recordings to date. By enabling event-related research with high-temporal precision, this method greatly enhances the utility of these recordings.

Mapping effective connectivity by virtually perturbing a surrogate brain

Effective connectivity (EC), which reflects the causal interactions between brain regions, is fundamental to understanding information processing in the brain; however, traditional methods for obtaining EC, which rely on neural responses to stimulation, are often invasive or limited in spatial coverage, making them unsuitable for whole-brain EC mapping in humans. Here, to address this gap, we introduce Neural Perturbational Inference (NPI), a data-driven framework for mapping whole-brain EC. NPI employs an artificial neural network trained to model large-scale neural dynamics, serving as a computational surrogate of the brain. By systematically perturbing all regions in the surrogate brain and analyzing the resulting responses in other regions, NPI maps the directionality, strength and excitatory/inhibitory properties of brain-wide EC. Validation of NPI on generative models with known ground-truth EC demonstrates its superiority over existing methods such as Granger causality and dynamic causal modeling. When applied to resting-state functional magnetic resonance imaging data across diverse datasets, NPI reveals consistent, structurally supported EC patterns. Furthermore, comparisons with cortico-cortical evoked potential data show a strong resemblance between NPI-inferred EC and real stimulation propagation patterns. By transitioning from correlational to causal understandings of brain functionality, NPI marks a stride in decoding the brain's functional architecture and facilitating both neuroscience studies and clinical applications.

Shared pathway-specific network mechanisms of dopamine and deep brain stimulation for the treatment of Parkinson's disease

Deep brain stimulation is a brain circuit intervention that can modulate distinct neural pathways for the alleviation of neurological symptoms in patients with brain disorders. In Parkinson's disease, subthalamic deep brain stimulation clinically mimics the effect of dopaminergic drug treatment, but the shared pathway mechanisms on cortex - basal ganglia networks are unknown. To address this critical knowledge gap, we combined fully invasive neural multisite recordings in patients undergoing deep brain stimulation surgery with normative MRI-based whole-brain connectomics. Our findings demonstrate that dopamine and stimulation exert distinct mesoscale effects through modulation of local neural population activity. In contrast, at the macroscale, stimulation mimics dopamine in its suppression of excessive interregional network synchrony associated with indirect and hyperdirect cortex - basal ganglia pathways. Our results provide a better understanding of the circuit mechanisms of dopamine and deep brain stimulation, laying the foundation for advanced closed-loop neurostimulation therapies.

Comparison of structural connectomes for modeling deep brain stimulation pathway activation

INTRODUCTION

Structural connectivity models of the brain are commonly employed to identify pathways that are directly activated during deep brain stimulation (DBS). However, various connectomes differ in the technical parameters, parcellation schemes, and methodological approaches used in their construction.

OBJECTIVE

The goal of this study was to compare and quantify variability in DBS pathway activation predictions when using different structural connectomes, while using identical electrode placements and stimulation volumes in the brain.

APPROACH

We analyzed four example structural connectomes: 1) Horn normative connectome (whole brain), 2) Yeh population-averaged tract-to-region pathway atlas (whole brain), 3) Petersen histology-based pathway atlas (subthalamic focused), and 4) Majtanik histology-based pathway atlas (anterior thalamus focused). DBS simulations were performed with each connectome, at four generalized locations for DBS electrode placement: 1) subthalamic nucleus, 2) anterior nucleus of thalamus, 3) ventral capsule, and 4) ventral intermediate nucleus of thalamus.

RESULTS

The choice of connectome used in the simulations resulted in notably distinct pathway activation predictions, and quantitative analysis indicated little congruence in the predicted patterns of brain network connectivity. The Horn and Yeh tractography-based connectomes provided estimates of DBS connectivity for any stimulation location in the brain, but have limitations in their anatomical validity. The Petersen and Majtanik histology-based connectomes are more anatomically realistic, but are only applicable to specific DBS targets because of their limited representation of pathways.

SIGNIFICANCE

The widely varying and inconsistent inferences of DBS network connectivity raises substantial concern regarding the general reliability of connectomic DBS studies, especially those that lack anatomical and/or electrophysiological validation in their analyses.

Spike-phase coupling of subthalamic neurons to posterior perisylvian cortex predicts speech sound accuracy

Speech provides a rich context for understanding how cortical interactions with the basal ganglia contribute to unique human behaviors, but opportunities for direct human intracranial recordings across cortical-basal ganglia networks are rare. Here we have recorded electrocorticographic signals in the cortex synchronously with single units in the basal ganglia during awake neurosurgeries where participants spoke syllable repetitions. We have discovered that individual subthalamic nucleus (STN) neurons have transient (200 ms) spike-phase coupling (SPC) events with multiple cortical regions. The spike timing of STN neurons is locked to the phase of theta-alpha oscillations in the supramarginal and posterior superior temporal gyrus during speech planning and production. Speech sound errors occur when this STN-cortical interaction is delayed. Our results suggest that timely interactions between the STN and the posterior perisylvian cortex support auditory-motor coordinate transformation or phonological working memory during speech planning. These findings establish a framework for understanding cortical-basal ganglia interaction in other human behaviors, and additionally indicate that firing-rate based models are insufficient for explaining basal ganglia circuit behavior.

Subthalamic Deep Brain Stimulation: Mapping Non-Motor Outcomes to Structural Connections

In Parkinson's Disease (PD), deep brain stimulation of the subthalamic nucleus (STN-DBS) reliably improves motor symptoms, and the circuits mediating these effects have largely been identified. However, non-motor outcomes are more variable, and it remains unclear which specific brain circuits need to be modulated or avoided to improve them. Since numerous non-motor symptoms potentially respond to DBS, it is challenging to independently identify the circuits mediating each one of them. Data compression algorithms such as principal component analysis (PCA) may provide a powerful alternative. This study aimed at providing a proof of concept for this approach by mapping changes along extensive score batteries to a few anatomical fiber bundles and, in turn, estimating changes in individual scores based on stimulation of these tracts. Retrospective data from 56 patients with PD and bilateral STN-DBS was included. The patients had undergone comprehensive clinical assessments covering changes in appetitive behaviors, mood, anxiety, impulsivity, cognition, and empathy. PCA was implemented to identify the main dimensions of neuropsychiatric and neuropsychological outcomes. Using DBS fiber filtering, we identified the structural connections whose stimulation was associated with change along these dimensions. Then, estimates of individual symptom outcomes were derived based on the stimulation of these connections by inverting the PCA. Finally, changes along a specific non-motor score were estimated in an independent validation dataset (N = 68) using the tract model. Four principal components were retained, which could be interpreted to reflect (i) general non-motor improvement; (ii) improvement of mood and cognition and worsening of trait impulsivity; (iii) improvement of cognition; and (iv) improvement of empathy and worsening of impulsive-compulsive behaviors. Each component was associated with the stimulation of spatially segregated fiber bundles connecting regions of the frontal cortex with the subthalamic nucleus. The extent of stimulation of these tracts was able to explain significant amounts of variance in outcomes for individual symptoms in the original cohort (circular analysis), as well as in the rank of depression outcomes in the independent validation cohort. Our approach represents an innovative concept for mapping changes along extensive score batteries to a few anatomical fiber bundles and could pave the way toward personalized deep brain stimulation.

A Self-Supporting Flexible Electrode for Tracking and Reversible Quantification of Mg2+ and Ca2+ in the Brains of Freely Behaving Animal

Monitoring dynamic neurochemical signals in the brain of free-moving animals remains great challenging in biocompatibility and direct implantation capability of current electrodes. Here we created a self-supporting polymer-based flexible microelectrode (rGPF) with sufficient bending stiffness for direct brain implantation without extra devices, but demonstrating low Young's modulus with remarkable biocompatibility and minimal position shifts. Meanwhile, screening by density functional theory (DFT) calculation, we designed and synthesized specific ligands targeting Mg2+ and Ca2+, and constructed Mg-E and Ca-E sensors with high selectivity, good reversibility, and fast response time, successfully monitoring Mg2+ and Ca2+ in vivo up to 90 days. Using this powerful tool, we discovered for the first time that, during the 4-aminopyridine-induced seizure in the live brain, extracellular Mg2+ inhibited Ca2+ influx. Moreover, the timing of initial changes in Mg2+ and Ca2+ levels during seizures aligned with neural pathways, which had not been previously reported.

Deep Brain Stimulation response circuits in Obsessive Compulsive Disorder

In the field of deep brain stimulation (DBS), two major themes are currently making significant progress. First, the framework of connectomic DBS, in which circuits that are associated with improvements of specific symptoms are described and targeted to improve and potentially personalize treatment. Second, the concept of brain sensing and adaptive DBS, which aims at identifying neural biomarkers that may guide stimulation in a closed-loop fashion. In DBS for Obsessive Compulsive Disorder (OCD), substantial progress has been made on both ends, over the last five years. Together, results begin to draw a picture of exactly which circuit is associated with treatment response, and how it may be affected by dysfunctional brain activity that may be attenuated using DBS. In turn, this knowledge, if further refined and validated, will define where, when, and how to stimulate which patients with OCD. We review the key studies from recent years with the aim to aggregate and condense findings along both spatial and temporal domains. The result is a concept that anatomically defines a circuit that is likely dysfunctional in patients with typical OCD phenotypes, and which may be adaptively targeted using DBS to maximally improve symptoms.

Invasive Brain Mapping Identifies Personalized Therapeutic Neuromodulation Targets for Obsessive-Compulsive Disorder

Deep brain stimulation has been used to treat severe, refractory obsessive-compulsive disorder (OCD) with variable outcomes across multiple anatomical targets. To overcome these limitations, we developed an invasive brain mapping paradigm in which electrodes were implanted across the OCD cortico-striato-thalamo-cortical circuit in a single individual. We then performed extensive stimulation mapping during a multi-day inpatient stay to identify personalized therapeutic targets and characterize their downstream circuit effects. We found two targets within the right ventral capsule (VC) that acutely reduced OCD symptoms. Prolonged VC stimulation suppressed high frequency activity within the structurally and functionally connected orbitofrontal cortex, which encoded the severity of OCD symptoms. These VC sites were implanted for DBS and combined stimulation of these targets led to a rapid therapeutic response. This case provides the first proof-of-concept that invasive brain mapping can be used to guide a novel personalized, multi-site neuromodulation approach to treat refractory OCD.

Subjective patient rating as a novel feedback signal for DBS programming in Parkinson's disease

BACKGROUND

Deep brain stimulation of the subthalamic nucleus (STN-DBS) effectively alleviates motor fluctuations in Parkinson's disease (PD). Optimal electrode placement and effective programming significantly influence outcomes. From a patient's perspective, DBS should relieve motor symptoms while avoiding side effects. However, there is a lack of programming routines that consider patients' subjective feedback for parameter adjustment.

OBJECTIVE

This study assessed the usefulness of patients' subjective ratings as feedback for DBS programming.

METHODS

We analyzed 260 DBS settings from 11 STN-DBS patients, pairing each volume of tissue activated (VTA) with a subjective rating measured by a visual analogue scale (VAS). We performed sweet spot mapping and connectivity analyses, utilizing voxel-wise and nonparametric permutation statistics to identify neuroanatomical regions and connectivity profiles associated with the highest VAS ratings. To validate our findings, we cross-validated the results in an independent test dataset of 6 patients (189 settings) to determine if the sweet spot and connectivity profile could predict the subjective patient perception.

RESULTS

VTAs with the highest VAS scores were localized to the dorsolateral STN, consistent with published sweet spots derived from clinical data. Connectivity with the supplementary motor area (SMA) and primary motor cortex (M1) was associated with a more positive subjective perception. Connectivity profiles derived from one dataset successfully predicted outcomes in an independent dataset, as validated through leave-one-cohort-out cross-validation.

CONCLUSIONS

Mapping patients' subjective perceptions using VAS yields conclusive anatomical results that align with objective clinical and imaging measures. VAS-guided programming could provide an additional feedback mechanism for both acute and chronic DBS parameter adjustments.

Network Localization of Pediatric Lesion-Induced Dystonia

OBJECTIVE

Dystonia is a movement disorder defined by involuntary muscle contractions leading to abnormal postures or twisting and repetitive movements. Classically dystonia has been thought of as a disorder of the basal ganglia, but newer results in idiopathic dystonia and lesion-induced dystonia in adults point to broader motor network dysfunction spanning the basal ganglia, cerebellum, premotor cortex, sensorimotor, and frontoparietal regions. It is unclear whether a similar network is shared between different etiologies of pediatric lesion-induced dystonia.

METHODS

Three cohorts of pediatric patients with lesion-induced dystonia were identified. The lesion etiologies included hypoxia, kernicterus, and stroke versus comparison subjects with acquired lesions not associated with dystonia. Multivariate lesion-symptom mapping and lesion network mapping were used to evaluate the anatomy and networks associated with dystonia.

RESULTS

Multivariate lesion-symptom mapping showed that lesions of the putamen and globus pallidus were associated with dystonia (r = 0.41, p < 0.001). Lesion network mapping using normative connectome data from healthy children demonstrated that these regional findings occurred within a common brain-wide network that involves the basal ganglia, anterior and medial cerebellum, and cortical regions that overlap the cingulo-opercular action-mode and somato-cognitive-action networks.

INTERPRETATION

We interpret these findings as novel evidence for a unified dystonia brain network that involves the somato-cognitive-action network, which is implicated in the coordination of movement. Elucidation of this network gives insight into the functional origins of dystonia and provides novel targets to investigate for therapeutic intervention. ANN NEUROL 2025.

Emerging Techniques for the Personalization of Deep Brain Stimulation Programming

The success of deep brain stimulation (DBS) relies on applying carefully titrated therapeutic stimulation at specific targets. Once implanted, the electrical stimulation parameters at each electrode contact can be modified. Iteratively adjusting the stimulation parameters enables testing for the optimal stimulation settings. Due to the large parameter space, the currently employed empirical testing of individual parameters based on acute clinical response is not sustainable. Within the constraints of short clinical visits, optimization is particularly challenging when clinical features lack immediate feedback, as seen in DBS for dystonia and depression and with the cognitive and axial side effects of DBS for Parkinson's disease. A personalized approach to stimulation parameter selection is desirable as the increasing complexity of modern DBS devices also expands the number of available parameters. This review describes three emerging imaging and electrophysiological methods of personalizing DBS programming. Normative connectome-base stimulation utilizes large datasets of normal or disease-matched connectivity imaging. The stimulation location for an individual patient can then be varied to engage regions associated with optimal connectivity. Electrophysiology-guided open- and closed-loop stimulation capitalizes on the electrophysiological recording capabilities of modern implanted devices to individualize stimulation parameters based on biomarkers of success or symptom onset. Finally, individual functional MRI (fMRI)-based approaches use fMRI during active stimulation to identify parameters resulting in characteristic patterns of functional engagement associated with long-term treatment response. Each method provides different but complementary information, and maximizing treatment efficacy likely requires a combined approach.

Engaging dystonia networks with subthalamic stimulation

Deep brain stimulation is an efficacious treatment for dystonia. While the internal pallidum serves as the primary target, recently, stimulation of the subthalamic nucleus (STN) has been investigated. However, optimal targeting within this structure and its surroundings have not been studied in depth. Indeed, 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 same target. Therefore, a thorough investigation of neural substrates underlying stimulation effects on dystonia signs and symptoms is warranted. Here, we analyze a multicenter cohort of isolated dystonia patients with subthalamic implantations (N = 58) and relate their stimulation sites to improvements of appendicular and cervical symptoms as well as blepharospasm. Stimulation of the ventral oral posterior nucleus of thalamus and surrounding regions were associated with improvements in cervical dystonia, while stimulation of the dorsolateral STN was associated with improvements in limb dystonia and blepharospasm. This dissociation was matched by structural connectivity analysis, where the cerebellothalamic, corticospinal, and pallidosubthalamic tracts were associated with improvements of cervical dystonia, while hyperdirect and subthalamopallidal pathways with alleviation of limb dystonia and blepharospasm. On the level of functional networks, improvements of limb dystonia were associated with connectivity to the corresponding somatotopic regions in the primary motor cortex, while alleviation of cervical dystonia to the cingulo-opercular network. These findings shed light on the pathophysiology of dystonia and may guide DBS targeting and programming in the future.

Therapeutic DBS for OCD Suppresses the Default Mode Network

Deep brain stimulation (DBS) of the anterior limb of the internal capsule (ALIC) is a circuit-based treatment for severe, refractory obsessive-compulsive disorder (OCD). The therapeutic effects of DBS are hypothesized to be mediated by direct modulation of a distributed cortico-striato-thalmo-cortical network underlying OCD symptoms. However, the exact underlying mechanism by which DBS exerts its therapeutic effects still remains unclear. In five participants receiving DBS for severe, refractory OCD (3 responders, 2 non-responders), we conducted a DBS On/Off cycling paradigm during the acquisition of functional MRI (23 fMRI runs) to determine the network effects of stimulation across a variety of bipolar configurations. We also performed tractography using diffusion-weighted imaging (DWI) to relate the functional impact of DBS to the underlying structural connectivity between active stimulation contacts and functional brain networks. We found that therapeutic DBS had a distributed effect, suppressing BOLD activity within regions such as the orbitofrontal cortex, dorsomedial prefrontal cortex, and subthalamic nuclei compared to non-therapeutic configurations. Many of the regions suppressed by therapeutic DBS were components of the default mode network (DMN). Moreover, the estimated stimulation field from the therapeutic configurations exhibited significant structural connectivity to core nodes of the DMN. Based upon these findings, we hypothesize that the suppression of the DMN by ALIC DBS is mediated by interruption of communication through structural white matter connections surrounding the DBS active contacts.

Functional anatomy of the subthalamic nucleus and the pathophysiology of cardinal features of Parkinson's disease unraveled by focused ultrasound ablation

The subthalamic nucleus (STN) modulates basal ganglia output and plays a fundamental role in the pathophysiology of Parkinson's disease (PD). Blockade/ablation of the STN improves motor signs in PD. We assessed the topography of focused ultrasound subthalamotomy (n = 39) by voxel-based lesion-symptom mapping to identify statistically validated brain voxels with the optimal effect against each cardinal feature and their respective cortical connectivity patterns by diffusion-weighted tractography. Bradykinesia and rigidity amelioration were associated with ablation of the rostral motor STN subregion connected to the supplementary motor and premotor cortices, whereas antitremor effect was explained by lesioning the posterolateral STN projection to the primary motor cortex. These findings were corroborated prospectively in another PD cohort (n = 12). This work concurs with recent deep brain stimulation findings that suggest different corticosubthalamic circuits underlying each PD cardinal feature. Our results provide sound evidence in humans of segregated anatomy of subthalamic-cortical connections and their distinct role in PD pathophysiology and normal motor control.

Psychiatric neuroimaging designs for individualised, cohort, and population studies

Psychiatric neuroimaging faces challenges to rigour and reproducibility that prompt reconsideration of the relative strengths and limitations of study designs. Owing to high resource demands and varying inferential goals, current designs differentially emphasise sample size, measurement breadth, and longitudinal assessments. In this overview and perspective, we provide a guide to the current landscape of psychiatric neuroimaging study designs with respect to this balance of scientific goals and resource constraints. Through a heuristic data cube contrasting key design features, we discuss a resulting trade-off among small sample, precision longitudinal studies (e.g., individualised studies and cohorts) and large sample, minimally longitudinal, population studies. Precision studies support tests of within-person mechanisms, via intervention and tracking of longitudinal course. Population studies support tests of generalisation across multifaceted individual differences. A proposed reciprocal validation model (RVM) aims to recursively leverage these complementary designs in sequence to accumulate evidence, optimise relative strengths, and build towards improved long-term clinical utility.

A human brain network linked to restoration of consciousness after deep brain stimulation

Disorders of consciousness (DoC) are states of impaired arousal or awareness. Deep brain stimulation (DBS) is a potential treatment, but outcomes vary, possibly due to differences in patient characteristics, electrode placement, or stimulation of specific brain networks. We studied 40 patients with DoC who underwent DBS targeting the thalamic centromedian-parafascicular complex. Better-preserved gray matter, especially in the striatum, correlated with consciousness improvement. Stimulation was most effective when electric fields extended into parafascicular and subparafascicular nuclei-ventral to the centromedian nucleus, near the midbrain-and when it engaged projection pathways of the ascending arousal network, including the hypothalamus, brainstem, and frontal lobe. Moreover, effective DBS sites were connected to networks similar to those underlying impaired consciousness due to generalized absence seizures and acquired lesions. These findings support the therapeutic potential of DBS for DoC, emphasizing the importance of precise targeting and revealing a broader link between effective DoC treatment and mechanisms underlying other conscciousness-impairing conditions.

One-Dimensional Implantable Sensors for Accurately Monitoring Physiological and Biochemical Signals

In recent years, one-dimensional (1D) implantable sensors have received considerable attention and rapid development in the biomedical field due to their unique structural characteristics and high integration capability. These sensors can be implanted into the human body with minimal invasiveness, facilitating real-time and accurate monitoring of various physiological and pathological parameters. This review examines the latest advancements in 1D implantable sensors, focusing on the material design of sensors, device integration, implantation methods, and the construction of the stable sensor-tissue interface. Furthermore, a comprehensive overview is provided regarding the applications and future research directions for 1D implantable sensors with an ultimate aim to promote their utilization in personalized healthcare and precision medicine.

Mesoscale Brain Mapping: Bridging Scales and Modalities in Neuroimaging - A Symposium Review

Advances in the spatiotemporal resolution and field-of-view of neuroimaging tools are driving mesoscale studies for translational neuroscience. On October 10, 2023, the Center for Mesoscale Mapping (CMM) at the Massachusetts General Hospital (MGH) Athinoula A. Martinos Center for Biomedical Imaging and the Massachusetts Institute of Technology (MIT) Health Sciences Technology based Neuroimaging Training Program (NTP) hosted a symposium exploring the state-of-the-art in this rapidly growing area of research. "Mesoscale Brain Mapping: Bridging Scales and Modalities in Neuroimaging" brought together researchers who use a broad range of imaging techniques to study brain structure and function at the convergence of the microscopic and macroscopic scales. The day-long event centered on areas in which the CMM has established expertise, including the development of emerging technologies and their application to clinical translational needs and basic neuroscience questions. The in-person symposium welcomed more than 150 attendees, including 57 faculty members, 61 postdoctoral fellows, 35 students, and four industry professionals, who represented institutions at the local, regional, and international levels. The symposium also served the training goals of both the CMM and the NTP. The event content, organization, and format were planned collaboratively by the faculty and trainees. Many CMM faculty presented or participated in a panel discussion, thus contributing to the dissemination of both the technologies they have developed under the auspices of the CMM and the findings they have obtained using those technologies. NTP trainees who benefited from the symposium included those who helped to organize the symposium and/or presented posters and gave "flash" oral presentations. In addition to gaining experience from presenting their work, they had opportunities throughout the day to engage in one-on-one discussions with visiting scientists and other faculty, potentially opening the door to future collaborations. The symposium presentations provided a deep exploration of the many technological advances enabling progress in structural and functional mesoscale brain imaging. Finally, students worked closely with the presenting faculty to develop this report summarizing the content of the symposium and putting it in the broader context of the current state of the field to share with the scientific community. We note that the references cited here include conference abstracts corresponding to the symposium poster presentations.

Analyses of single-cell and bulk RNA sequencing combined with machine learning reveal the expression patterns of disrupted mitophagy in schizophrenia

Background

Mitochondrial dysfunction is an important factor in the pathogenesis of schizophrenia. However, the relationship between mitophagy and schizophrenia remains to be elucidated.

Methods

Single-cell RNA sequencing datasets of peripheral blood and brain organoids from SCZ patients and healthy controls were retrieved. Mitophagy-related genes that were differentially expressed between the two groups were screened. The diagnostic model based on key mitophagy genes was constructed using two machine learning methods, and the relationship between mitophagy and immune cells was analyzed. Single-cell RNA sequencing data of brain organoids was used to calculate the mitophagy score (Mitoscore).

Results

We found 7 key mitophagy genes to construct a diagnostic model. The mitophagy genes were related to the infiltration of neutrophils, activated dendritic cells, resting NK cells, regulatory T cells, resting memory T cells, and CD8 T cells. In addition, we identified 12 cell clusters based on the Mitoscore, and the most abundant neurons were further divided into three subgroups. Results at the single-cell level showed that Mitohigh_Neuron established a novel interaction with endothelial cells via SPP1 signaling pathway, suggesting their distinct roles in SCZ pathogenesis.

Conclusion

We identified a mitophagy signature for schizophrenia that provides new insights into disease pathogenesis and new possibilities for its diagnosis and treatment.

Concerning neuromodulation as treatment of neurological and neuropsychiatric disorder: Insights gained from selective targeting of the subthalamic nucleus, para-subthalamic nucleus and zona incerta in rodents

Neuromodulation such as deep brain stimulation (DBS) is advancing as a clinical intervention in several neurological and neuropsychiatric disorders, including Parkinson's disease, dystonia, tremor, and obsessive-compulsive disorder (OCD) for which DBS is already applied to alleviate severely afflicted individuals of symptoms. Tourette syndrome and drug addiction are two additional disorders for which DBS is in trial or proposed as treatment. However, some major remaining obstacles prevent this intervention from reaching its full therapeutic potential. Side-effects have been reported, and not all DBS-treated individuals are relieved of their symptoms. One major target area for DBS electrodes is the subthalamic nucleus (STN) which plays important roles in motor, affective and associative functions, with impact on for example movement, motivation, impulsivity, compulsivity, as well as both reward and aversion. The multifunctionality of the STN is complex. Decoding the anatomical-functional organization of the STN could enhance strategic targeting in human patients. The STN is located in close proximity to zona incerta (ZI) and the para-subthalamic nucleus (pSTN). Together, the STN, pSTN and ZI form a highly heterogeneous and clinically important brain area. Rodent-based experimental studies, including opto- and chemogenetics as well as viral-genetic tract tracings, provide unique insight into complex neuronal circuitries and their impact on behavior with high spatial and temporal precision. This research field has advanced tremendously over the past few years. Here, we provide an inclusive review of current literature in the pre-clinical research fields centered around STN, pSTN and ZI in laboratory mice and rats; the three highly heterogeneous and enigmatic structures brought together in the context of relevance for treatment strategies. Specific emphasis is placed on methods of manipulation and behavioral impact.

Cognitive sequences in obsessive-compulsive disorder are supported by frontal cortex ramping activity and mediated by symptom severity

Completing sequences is part of everyday life. Many such sequences can be considered abstract - that is, defined by a rule that governs the order but not the identity of individual steps (e.g., getting dressed for work). Over-engagement in ritualistic and repetitive behaviors seen in obsessive-compulsive disorder (OCD) suggests that abstract sequences may be disrupted in this disorder. Previous work has shown the necessity of the rostrolateral prefrontal cortex (RLPFC) for abstract sequence processing and that neural activity increases (ramps) in this region across sequences (Desrochers et al., 2015, 2019). Neurobiological models of the cortico-striatal-thalamo-cortical (CSTC) loops describe prefrontal circuitry connected to RLPFC and that is believed to be dysfunctional in OCD. As a potential extension of these models, we hypothesized that neural dynamics of RLPFC could be disrupted in OCD during abstract sequence engagement. We found that neural dynamics in RLPFC did not differ between OCD and healthy controls (HCs), but that increased ramping in pregenual anterior cingulate cortex (rACC), and superior frontal sulcus (SFS) dissociates these two groups in an abstract sequence paradigm. Further, we found that anxiety and depressive symptoms mediated the relationship between observed neural activity and behavioral differences observed in the task. This study highlights the importance of investigating ramping as a relevant neural dynamic during sequences and suggests expansion of current neurobiological models to include regions that support sequential behavior in OCD. Further, our results may point to novel regions to consider for neuromodulatory treatments of OCD in the future.

Default mode network dynamics: An integrated neurocircuitry perspective on social dysfunction in human brain disorders

Our intricate social brain is implicated in a range of brain disorders, where social dysfunction emerges as a common neuropsychiatric feature cutting across diagnostic boundaries. Understanding the neurocircuitry underlying social dysfunction and exploring avenues for its restoration could present a transformative and transdiagnostic approach to overcoming therapeutic challenges in these disorders. The brain's default mode network (DMN) plays a crucial role in social functioning and is implicated in various neuropsychiatric conditions. By thoroughly examining the current understanding of DMN functionality, we propose that the DMN integrates diverse social processes, and disruptions in brain communication at regional and network levels due to disease hinder the seamless integration of these social functionalities. Consequently, this leads to an altered balance between self-referential and attentional processes, alongside a compromised ability to adapt to social contexts and anticipate future social interactions. Looking ahead, we explore how adopting an integrated neurocircuitry perspective on social dysfunction could pave the way for innovative therapeutic approaches to address brain disorders.

Subthalamic and pallidal oscillations and their couplings reflect dystonia severity and improvements by deep brain stimulation

BACKGROUND

Deep brain stimulation (DBS) targeting the globus pallidus internus (GPi) and subthalamic nucleus (STN) is employed for the treatment of dystonia. Pallidal low-frequency oscillations have been proposed as a pathophysiological marker for dystonia. However, the role of subthalamic oscillations and STN-GPi coupling in relation to dystonia remains unclear.

OBJECTIVE

We aimed to explore oscillatory activities within the STN-GPi circuit and their correlation with the severity of dystonia and efficacy achieved by DBS treatment.

METHODS

Local field potentials were recorded simultaneously from the STN and GPi from 13 dystonia patients. Spectral power analysis was conducted for selected frequency bands from both nuclei, while power correlation and the weighted phase lag index were used to evaluate power and phase couplings between these two nuclei, respectively. These features were incorporated into generalized linear models to assess their associations with dystonia severity and DBS efficacy.

RESULTS

The results revealed that pallidal theta power, subthalamic beta power and subthalamic-pallidal theta phase coupling and beta power coupling all correlated with clinical severity. The model incorporating all selected features predicts empirical clinical scores and DBS-induced improvements, whereas the model relying solely on pallidal theta power failed to demonstrate significant correlations.

CONCLUSIONS

Beyond pallidal theta power, subthalamic beta power, STN-GPi couplings in theta and beta bands, play a crucial role in understanding the pathophysiological mechanism of dystonia and developing optimal strategies for DBS.

Exploring the electrophysiology of Parkinson's disease with magnetoencephalography and deep brain recordings

Aberrant information processing in the basal ganglia and connected cortical areas are key to many neurological movement disorders such as Parkinson's disease. Investigating the electrophysiology of this system is difficult in humans because non-invasive methods, such as electroencephalography or magnetoencephalography, have limited sensitivity to deep brain areas. Recordings from electrodes implanted for therapeutic deep brain stimulation, in contrast, provide clear deep brain signals but are not suited for studying cortical activity. Therefore, we combine magnetoencephalography and local field potential recordings from deep brain stimulation electrodes in individuals with Parkinson's disease. Here, we make these data available, inviting a broader scientific community to explore the dynamics of neural activity in the subthalamic nucleus and its functional connectivity to cortex. The dataset encompasses resting-state recordings, plus two motor tasks: static forearm extension and self-paced repetitive fist clenching. Most patients were recorded both in the medicated and the unmedicated state. Along with the raw data, we provide metadata on channels, events and scripts for pre-processing to help interested researchers get started.

Therapeutic DBS for OCD Suppresses the Default Mode Network

Background

Deep brain stimulation (DBS) of the anterior limb of the internal capsule (ALIC) is an emerging treatment for severe, refractory obsessive-compulsive disorder (OCD). The therapeutic effects of DBS are hypothesized to be mediated by direct modulation of a distributed cortico-striato-thalmo-cortical network underlying OCD symptoms. However, the exact underlying mechanism by which DBS exerts its therapeutic effects still remains unclear.

Method

In five participants receiving DBS for severe, refractory OCD (3 responders, 2 non-responders), we conducted a DBS On/Off cycling paradigm during the acquisition of functional MRI to determine the network effects of stimulation across a variety of bipolar configurations. We also performed tractography using diffusion-weighted imaging (DWI) to relate the functional impact of DBS to the underlying structural connectivity between active stimulation contacts and functional brain networks.

Results

We found that therapeutic DBS had a distributed effect, suppressing BOLD activity within regions such as the orbitofrontal cortex, dorsomedial prefrontal cortex, and subthalamic nuclei compared to non-therapeutic configurations. Many of the regions suppressed by therapeutic DBS were components of the default mode network (DMN). Moreover, the estimated stimulation field from the therapeutic configurations exhibited significant structural connectivity to core nodes of the DMN.

Conclusions

Therapeutic DBS for OCD suppresses BOLD activity within a distributed set of regions within the DMN relative to non-therapeutic configurations. We propose that these effects may be mediated by interruption of communication through structural white matter connections surrounding the DBS active contacts.

Role of Prefrontal Cortex Circuitry in Maintaining Social Homeostasis

Homeostasis is a fundamental concept in biology and ensures the stability of life by maintaining the constancy of physiological processes. Recent years have witnessed a surge in research interest in these physiological processes, with a growing focus on understanding the mechanisms underlying social homeostasis. This shift in focus underscores our increasing understanding of the importance of social interactions and their impact on individual well-being. In this review, we explore the interconnected research across 3 primary categories: understanding the neural mechanisms influencing set points, defining contemporary factors that can disrupt social homeostasis, and identifying the potential contributions of social homeostatic failure in the development of psychiatric diseases. We also delve into the role of the prefrontal cortex and its circuitry in regulating social behavior, decision-making processes, and the manifestation of neuropsychiatric disorders, such as depression and anxiety. Finally, we examine the influence of more recent factors such as growing social media exposure and the COVID-19 pandemic on mental health, highlighting their disruptive effects. We also identify gaps in current literature through the analysis of research trends and propose future research directions to advance our understanding of social homeostasis, with implications for mental health interventions.

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.

Deep brain stimulation of the subthalamic nucleus for Parkinson's disease: A network imaging marker of the treatment response

Subthalamic nucleus deep brain stimulation (STN-DBS) alleviates motor symptoms of Parkinson's disease (PD), thereby improving quality of life. However, quantitative brain markers to evaluate DBS responses and select suitable patients for surgery are lacking. Here, we used metabolic brain imaging to identify a reproducible STN-DBS network for which individual expression levels increased with stimulation in proportion to motor benefit. Of note, measurements of network expression from metabolic and BOLD imaging obtained preoperatively predicted motor outcomes determined after DBS surgery. Based on these findings, we computed network expression in 175 PD patients, with time from diagnosis ranging from 0 to 21 years, and used the resulting data to predict the outcome of a potential STN-DBS procedure. While minimal benefit was predicted for patients with early disease, the proportion of potential responders increased after 4 years. Clinically meaningful improvement with stimulation was predicted in 18.9 - 27.3% of patients depending on disease duration.

Network localization of pediatric lesion-induced dystonia

Objective

Dystonia is a movement disorder defined by involuntary muscle contractions leading to abnormal postures or twisting and repetitive movements. Classically dystonia has been thought of as a disorder of the basal ganglia, but newer results in idiopathic dystonia and lesion-induced dystonia in adults point to broader motor network dysfunction spanning the basal ganglia, cerebellum, premotor cortex, sensorimotor, and frontoparietal regions. It is unclear whether a similar network is shared between different etiologies of pediatric lesion-induced dystonia.

Methods

Three cohorts of pediatric patients with lesion-induced dystonia were identified. The lesion etiologies included hypoxia, kernicterus, and stroke versus comparison subjects with acquired lesions not associated with dystonia. Multivariate lesion-symptom mapping and lesion network mapping were used to evaluate the anatomy and networks associated with dystonia.

Results

Multivariate lesion-symptom mapping showed that lesions of the putamen (stroke: r = 0.50, p <0.01; hypoxia, r = 0.64, p <0.001) and globus pallidus (kernicterus, r = 0.61, p <0.01) were associated with dystonia. Lesion network mapping using normative connectome data from healthy children demonstrated that these regional findings occurred within a common brain-wide network that involves the basal ganglia, anterior and medial cerebellum, and cortical regions that overlap the cingulo-opercular and somato-cognitive-action networks.

Interpretation

We interpret these findings as novel evidence for a unified dystonia brain network that involves the somato-cognitive-action network, which is involved in higher order coordination of movement. Elucidation of this network gives insight into the functional origins of dystonia and provides novel targets to investigate for therapeutic intervention.

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.