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Abstract The rewards that we get from our choices and actions can have a major influence on our future behavior. Understanding how reward biasing of behavior is implemented in the brain is important for many reasons, including the fact that diminution in reward biasing is a hallmark of clinical depression. We hypothesized that reward biasing is mediated by the anterior cingulate cortex (ACC), a cortical hub region associated with the integration of reward and executive control and with the etiology of depression. To test this hypothesis, we recorded neural activity during a biased judgment task in patients undergoing intracranial monitoring for either epilepsy or major depressive disorder. We found that beta (12–30 Hz) oscillations in the ACC predicted both associated reward and the size of the choice bias, and also tracked reward receipt, thereby predicting bias on future trials. We found reduced magnitude of bias in depressed patients, in whom the beta-specific effects were correspondingly reduced. Our findings suggest that ACC beta oscillations may orchestrate the learning of reward information to guide adaptive choice, and, more broadly, suggest a potential biomarker for anhedonia and point to future development of interventions to enhance reward impact for therapeutic benefit.

Prefrontal circuits in the human brain play an important role in cognitive and affective processing. Neuromodulation therapies delivered to certain key hubs within these circuits are being used with increasing frequency to treat a host of neuropsychiatric disorders. However, the detailed neurophysiological effects of stimulation to these hubs are largely unknown. Here, we performed intracranial recordings across prefrontal networks while delivering electrical stimulation to two well-established white matter hubs involved in cognitive regulation and depression: the subcallosal cingulate (SCC) and ventral capsule/ventral striatum (VC/VS). We demonstrate a shared frontotemporal circuit consisting of the ventromedial prefrontal cortex, amygdala, and lateral orbitofrontal cortex where gamma oscillations are differentially modulated by stimulation target. Additionally, we found participant-specific responses to stimulation in the dorsal anterior cingulate cortex and demonstrate the capacity for further tuning of neural activity using current-steered stimulation. Our findings indicate a potential neurophysiological mechanism for the dissociable therapeutic effects seen across the SCC and VC/VS targets for psychiatric neuromodulation and our results lay the groundwork for personalized, network-guided neurostimulation therapy.

Objective.Despite advances in the treatment of psychiatric diseases, currently available therapies do not provide sufficient and durable relief for as many as 30–40% of patients. Neuromodulation, including deep brain stimulation (DBS), has emerged as a potential therapy for persistent disabling disease, however it has not yet gained widespread adoption. In 2016, the American Society for Stereotactic and Functional Neurosurgery (ASSFN) convened a meeting with leaders in the field to discuss a roadmap for the path forward. A follow-up meeting in 2022 aimed to review the current state of the field and to identify critical barriers and milestones for progress.Design.The ASSFN convened a meeting on June 3, 2022 in Atlanta, Georgia and included leaders from the fields of neurology, neurosurgery, and psychiatry along with colleagues from industry, government, ethics, and law. The goal was to review the current state of the field, assess for advances or setbacks in the interim six years, and suggest a future path forward. The participants focused on five areas of interest: interdisciplinary engagement, regulatory pathways and trial design, disease biomarkers, ethics of psychiatric surgery, and resource allocation/prioritization. The proceedings are summarized here.Conclusion.The field of surgical psychiatry has made significant progress since our last expert meeting. Although weakness and threats to the development of novel surgical therapies exist, the identified strengths and opportunities promise to move the field through methodically rigorous and biologically-based approaches. The experts agree that ethics, law, patient engagement, and multidisciplinary teams will be critical to any potential growth in this area.

Obsessive-compulsive disorder (OCD) affects 1–2% of children and is associated with functional impairment and diminished quality of life. Several treatments are efficacious: cognitive behavioral therapy (CBT) with exposure and response prevention, serotonin reuptake inhibitor (SRI) monotherapy, and combined treatment (SRI ​+ ​CBT). Expert clinician-informed practice parameters suggest that youth with mild to moderate OCD should be treated initially with CBT yet SRIs are frequently employed as the first-line intervention or in combination with psychotherapy in applied practice. Empirical data to guide SRI discontinuation in pediatric OCD are very limited. This study, Promoting OCD Wellness and Resiliency (POWER), aims to address this gap through a two phase, double-blinded, placebo-controlled, randomized controlled non-inferiority trial with the purpose of evaluating whether youth with OCD on an SRI can discontinue their medication after successful CBT augmentation and maintain wellness for a period of 24 weeks during which they receive maintenance CBT that models standard-of-care. In this paper we describe the rationale and methodological design of the POWER study.

Deep brain stimulation (DBS) therapies have shown clinical success in the treatment of a number of neurological illnesses, including obsessive-compulsive disorder, epilepsy, and Parkinson’s disease. An emerging strategy for increasing the efficacy of DBS therapies is to develop closed-loop, adaptive DBS systems that can sense biomarkers associated with particular symptoms and in response, adjust DBS parameters in real-time. The development of such systems requires extensive analysis of the underlying neural signals while DBS is on, so that candidate biomarkers can be identified and the effects of varying the DBS parameters can be better understood. However, DBS creates high amplitude, high frequency stimulation artifacts that prevent the underlying neural signals and thus the biological mechanisms underlying DBS from being analyzed. Additionally, DBS devices often require low sampling rates, which alias the artifact frequency, and rely on wireless data transmission methods that can create signal recordings with missing data of unknown length. Thus, traditional artifact removal methods cannot be applied to this setting. We present a novel periodic artifact removal algorithm for DBS applications that can accurately remove stimulation artifacts in the presence of missing data and in some cases where the stimulation frequency exceeds the Nyquist frequency. The numerical examples suggest that, if implemented on dedicated hardware, this algorithm has the potential to be used in embedded closed-loop DBS therapies to remove DBS stimulation artifacts and hence, to aid in the discovery of candidate biomarkers in real-time. Code for our proposed algorithm is publicly available on Github.

The deep brain stimulation (DBS) Think Tank X was held on August 17–19, 2022 in Orlando FL. The session organizers and moderators were all women with the theme women in neuromodulation. Dr. Helen Mayberg from Mt. Sinai, NY was the keynote speaker. She discussed milestones and her experiences in developing depression 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 the logistical and ethical issues facing the field. The consensus among the DBS Think Tank X speakers was that DBS has continued to expand in scope however several indications have reached the “trough of disillusionment.” DBS for depression was considered as “re-emerging” and approaching a slope of enlightenment. DBS for depression will soon re-enter clinical trials. The group estimated that globally more than 244,000 DBS devices have been implanted for neurological and neuropsychiatric disorders. This year’s meeting was focused on advances in the following areas: neuromodulation in Europe, Asia, and Australia; cutting-edge technologies, closed loop DBS, DBS tele-health, neuroethics, lesion therapy, interventional psychiatry, and adaptive DBS.

Bidirectional deep brain stimulation (DBS) platforms have enabled a surge in hours of recordings in naturalistic environments, allowing further insight into neurological and psychiatric disease states. However, high amplitude, high frequency stimulation generates artifacts that contaminate neural signals and hinder our ability to interpret the data. This is especially true in psychiatric disorders, for which high amplitude stimulation is commonly applied to deep brain structures where the native neural activity is miniscule in comparison. Here, we characterized artifact sources in recordings from a bidirectional DBS platform, the Medtronic Summit RC + S, with the goal of optimizing recording configurations to improve signal to noise ratio (SNR). Data were collected from three subjects in a clinical trial of DBS for obsessive-compulsive disorder. Stimulation was provided bilaterally to the ventral capsule/ventral striatum (VC/VS) using two independent implantable neurostimulators. We first manipulated DBS amplitude within safe limits (2–5.3 mA) to characterize the impact of stimulation artifacts on neural recordings. We found that high amplitude stimulation produces slew overflow, defined as exceeding the rate of change that the analog to digital converter can accurately measure. Overflow led to expanded spectral distortion of the stimulation artifact, with a six fold increase in the bandwidth of the 150.6 Hz stimulation artifact from 147–153 to 140–180 Hz. By increasing sense blank values during high amplitude stimulation, we reduced overflow by as much as 30% and improved artifact distortion, reducing the bandwidth from 140–180 Hz artifact to 147–153 Hz. We also identified artifacts that shifted in frequency through modulation of telemetry parameters. We found that telemetry ratio changes led to predictable shifts in the center-frequencies of the associated artifacts, allowing us to proactively shift the artifacts outside of our frequency range of interest. Overall, the artifact characterization methods and results described here enable increased data interpretability and unconstrained biomarker exploration using data collected from bidirectional DBS devices.

Recent advances in wireless data transmission technology have the potential to revolutionize clinical neuroscience. Today sensing-capable electrical stimulators, known as “bidirectional devices”, are used to acquire chronic brain activity from humans in natural environments. However, with wireless transmission come potential failures in data transmission, and not all available devices correctly account for missing data or provide precise timing for when data losses occur. Our inability to precisely reconstruct time-domain neural signals makes it difficult to apply subsequent neural signal processing techniques and analyses. Here, our goal was to accurately reconstruct time-domain neural signals impacted by data loss during wireless transmission. Towards this end, we developed a method termed Periodic Estimation of Lost Packets (PELP). PELP leverages the highly periodic nature of stimulation artifacts to precisely determine when data losses occur. Using simulated stimulation waveforms added to human EEG data, we show that PELP is robust to a range of stimulation waveforms and noise characteristics. Then, we applied PELP to local field potential (LFP) recordings collected using an implantable, bidirectional DBS platform operating at various telemetry bandwidths. By effectively accounting for the timing of missing data, PELP enables the analysis of neural time series data collected via wireless transmission—a prerequisite for better understanding the brain-behavior relationships underlying neurological and psychiatric disorders.

A brief, parent-led, transdiagnostic cognitive behavioral therapy (CBT) approach demonstrated utility among youth struggling with emotional problems during the COVID-19 pandemic. Homework completion between sessions is directly associated with psychotherapy treatment outcomes in non-parent-led CBT interventions. The present study sought to examine the relationship between homework completion and treatment response in a parent-led transdiagnostic CBT protocol. The first aim was to determine if completion of between session CBT homework was associated with change in symptom severity. The second aim was to determine if pre-treatment anxiety severity, social anxiety severity, and depressive symptoms were associated with treatment outcomes. One-hundred twenty-nine parents of youth (ages 5-13) with significant emotional problems received 6 sessions of telehealth parent-led CBT during the COVID-19 pandemic. Data on children's anxiety symptomology, clinical severity, homework compliance, depression, family relationships, perceptions on the impacts of the pandemic, treatment response, and therapists rating of symptom improvement were collected. Homework completion explained 9% of the variance in symptom improvement at post-treatment. Greater homework completion was associated with a significantly higher odds of treatment response (OR = 1.52, p = 0.001). Child anxiety severity, depressive symptoms, family relationships, and perceptions on the impacts of the COVID-19 pandemic were not significantly related to treatment outcome. Completion of homework predicted treatment outcomes in parent-led, transdiagnostic CBT for youth with emotional problems during the COVID-19 pandemic, while controlling for parent-rated anxiety, depression, family relationships, and COVID-related distress. Enhancing and targeting homework compliance between CBT sessions should be a central element of parent-led treatment.

This research study provides patient and caregiver perspectives as to whether or not to undergo adaptive deep brain stimulation (aDBS) research. A total of 51 interviews were conducted in a multi-site study including patients undergoing aDBS and their respective caregivers along with persons declining aDBS. Reasons highlighted for undergoing aDBS included hopes for symptom alleviation, declining quality of life, desirability of being in research, and altruism. The primary reasons for not undergoing aDBS issues were practical rather than specific to aDBS technology, although some persons highlighted a desire to not be the first to trial the new technology. These themes are discussed in the context of “push” factors wherein any form of surgical intervention is preferable to none and “pull” factors wherein opportunities to contribute to science combine with hopes and/or expectations for the alleviation of symptoms. We highlight the significance of study design in decision making. aDBS is an innovative technology and not a completely new technology. Many participants expressed value in being part of research as an important consideration. We suggest that there are important implications when comparing patient perspectives vs. theoretical perspectives on the choice for or against aDBS. Additionally, it will be important how we communicate with patients especially in reference to the complexity of study design. Ultimately, this study reveals that there are benefits and potential risks when choosing a research study that involves implantation of a medical device.

Hurricane Harvey was one of the most destructive hurricanes in U.S. history, resulting in widespread flooding and property damage in the greater Houston-metropolitan area. This study aims to characterize a group of treatment-seeking youth and adults up to 2.5 years following Hurricane Harvey. A total of 154 children, 165 adolescents, and 531 adults who presented to publicly-funded mental health services were assessed on demographics, depressive and anxiety symptomatology, and hurricane impact. Age, sex, race/ethnicity, family/social support, time since the hurricane, and hurricane impact were examined as correlates of depressive and anxiety symptoms at treatment initiation. Overall, participants presented with elevated depressive and anxiety symptoms to the clinic. Greater hurricane impact was correlated with depressive and anxiety symptoms in adults and adolescents, but not in children. In addition, poorer family/social support was linked to greater anxiety in children and higher depression scores in children and adolescents. Adolescent females had higher anxiety and depression than adolescent males. Days since Harvey and anxiety symptoms were negatively associated for adults. Clinical and research implications for psychological distress in the medium-to-long-term post-natural disaster period are discussed.

Objective: To improve the ability of psychiatry researchers to build, deploy, maintain, reproduce, and share their own psychophysiological tasks. Psychophysiological tasks are a useful tool for studying human behavior driven by mental processes such as cognitive control, reward evaluation, and learning. Neural mechanisms during behavioral tasks are often studied via simultaneous electrophysiological recordings. Popular online platforms such as Amazon Mechanical Turk (MTurk) and Prolific enable deployment of tasks to numerous participants simultaneously. However, there is currently no task-creation framework available for flexibly deploying tasks both online and during simultaneous electrophysiology. Methods: We developed a task creation template, termed Honeycomb, that standardizes best practices for building jsPsych-based tasks. Honeycomb offers continuous deployment configurations for seamless transition between use in research settings and at home. Further, we have curated a public library, termed BeeHive, of ready-to-use tasks. Results: We demonstrate the benefits of using Honeycomb tasks with a participant in an ongoing study of deep brain stimulation for obsessive compulsive disorder, who completed repeated tasks both in the clinic and at home. Conclusion: Honeycomb enables researchers to deploy tasks online, in clinic, and at home in more ecologically valid environments and during concurrent electrophysiology.

Summary: Advances in therapeutic neuromodulation devices have enabled concurrent stimulation and electrophysiology in the central nervous system. However, stimulation artifacts often obscure the sensed underlying neural activity. Here, we develop a method, termed Period-based Artifact Reconstruction and Removal Method (PARRM), to remove stimulation artifacts from neural recordings by leveraging the exact period of stimulation to construct and subtract a high-fidelity template of the artifact. Benchtop saline experiments, computational simulations, five unique in vivo paradigms across animal and human studies, and an obscured movement biomarker are used for validation. Performance is found to exceed that of state-of-the-art filters in recovering complex signals without introducing contamination. PARRM has several advantages: (1) it is superior in signal recovery; (2) it is easily adaptable to several neurostimulation paradigms; and (3) it has low complexity for future on-device implementation. Real-time artifact removal via PARRM will enable unbiased exploration and detection of neural biomarkers to enhance efficacy of closed-loop therapies. Motivation: Electrophysiological recordings concurrent with electrical stimulation of the brain and spinal cord are often corrupted by stimulation artifact. The removal of stimulation artifact is a necessary step toward identifying neural biomarkers that can be consistently used to titrate neuromodulation therapies or discover the underlying disease neuropathology. Thus, we developed a Period-based Artifact Reconstruction and Removal Method (PARRM) to provide a solution to removing such artifacts from low- and high-sample-rate recordings. PARRM is adaptive to changes in artifact shape, is robust to aliasing, and has low computational overhead readily implementable for use in real time. Our method aims to enable the investigation, and eventual development, of closed-loop neuromodulation therapies.

Purpose: Using data from a randomized clinical trial evaluating cognitive behavioral therapy (CBT) for children with autism and co-occurring anxiety, this study examined the relationship between autism features and anxiety symptoms throughout CBT. Methods: Two multilevel mediation analyses were run which examined the mediating role of changes in anxiety for changes in two core features of autism: (a) repetitive and restrictive behaviors (RRBs); and (b) social communication/interaction impairments, between pre- and post-treatment. Results: Indirect effects between time and autism characteristics were significant for both models, indicating that as anxiety changes, so do RRBs and social communication/interaction as the outcomes respectively. Conclusion: Findings suggest a bidirectional relationship between anxiety and autism features. Implications of these findings are discussed.

Mental disorders are a leading cause of disability worldwide, and available treatments have limited efficacy for severe cases unresponsive to conventional therapies. Neurosurgical interventions, such as lesioning procedures, have shown success in treating refractory cases of mental illness, but may have irreversible side effects. Neuromodulation therapies, specifically Deep Brain Stimulation (DBS), may offer similar therapeutic benefits using a reversible (explantable) and adjustable platform. Early DBS trials have been promising, however, pivotal clinical trials have failed to date. These failures may be attributed to targeting, patient selection, or the “open-loop” nature of DBS, where stimulation parameters are chosen ad hoc during infrequent visits to the clinician’s office that take place weeks to months apart. Further, the tonic continuous stimulation fails to address the dynamic nature of mental illness; symptoms often fluctuate over minutes to days. Additionally, stimulation-based interventions can cause undesirable effects if applied when not needed. A responsive, adaptive DBS (aDBS) system may improve efficacy by titrating stimulation parameters in response to neural signatures (i.e., biomarkers) related to symptoms and side effects. Here, we present rationale for the development of a responsive DBS system for treatment of refractory mental illness, detail a strategic approach for identification of electrophysiological and behavioral biomarkers of mental illness, and discuss opportunities for future technological developments that may harness aDBS to deliver improved therapy.

Objective: To examine the psychometric properties of the Chinese version of the Yale-Brown Obsessive Compulsive Scale – Second Edition (Y-BOCS-II). Method: A total of 86 adults with a primary diagnosis of obsessive-compulsive disorder (OCD), ranging in age from 15 to 78 years, participated in the study. Participants were administered the Y-BOCS-II by a trained clinician who also rated overall illness severity on two additional measures. Patients completed the Obsessive Compulsive Inventory-Revised and Depression Anxiety Stress Scale-21. Results: Results indicated high internal consistency and fair 1-week test retest reliability. The Y-BOCS-II scales correlated strongly with clinician-rated obsessive-compulsive severity and modestly with self-reported obsessive-compulsive symptom frequency and distress. The relationship between Y-BOCS-II total score and depressive and anxiety symptoms was strong, which may reflect high rates of comorbid conditions in this sample or the linkage between obsessive-compulsive symptom severity and distress. Factor analysis demonstrated a two-factor structure consisting of obsession and compulsion factors, with interference due to obsessions cross-loading. Conclusions: Overall, these results support the use of the Y-BOCS-II among individuals from China. Future study by an independent group is necessary to replicate these findings, as well as investigate interrater reliability and treatment sensitivity.

Obsessive compulsive disorder (OCD) is a common, disabling psychiatric disease characterized by persistent, intrusive thoughts and ritualistic, repetitive behaviors. Deep brain stimulation (DBS) is thought to alleviate OCD symptoms by modulating underlying disturbances in normal cortico-striato-thalamo-cortical (CSTC) circuitry. Stimulation of the ventral portion of the anterior limb of the internal capsule (ALIC) and underlying ventral striatum (“ventral capsule/ventral striatum” or “VC/VS” target) received U.S. FDA approval in 2009 for patients with severe, treatment-refractory OCD. Over the decades, DBS surgical outcome studies have led to an evolution in the electrical stimulation target. In parallel, advancements in neuroimaging techniques have allowed investigators to better visualize and define CSTC circuits underlying the pathophysiology of OCD. A critical analysis of these new data suggests that the therapeutic mechanism of DBS for OCD likely involves neuromodulation of a widespread cortical/subcortical network, accessible by targeting fiber bundles in the ventral ALIC that connect broad network regions. Future studies will include advances in structural and functional imaging, analysis of physiological recordings, and utilization of next-generation DBS devices. These tools will enable patient-specific optimization of DBS therapy, which will hopefully further improve outcomes.

This trial examined stepped-care cognitive-behavioral treatment (CBT) among 96 autistic youth with co-occurring anxiety. Step 1 included an open trial of parent-led, therapist-guided bibliotherapy. Step 2 was family-based CBT for those who did not respond to Step 1 or maintenance for those who did. Eighteen participants (28%) who completed Step 1 responded. Responders reported significantly lower pre-treatment anxiety, internalizing symptoms, and functional impairment than non-responders. After Steps 1 and 2, 80% of completers (55% intent-to-treat) were responders. Anxiety, impairment, and ASD-related impairments significantly improved. Youth in maintenance experienced faster improvement through post-treatment, though there were no group differences at 3-month-follow-up. A stepped approach may help some individuals in Step 1, particularly those who are less anxious.

Background: Medication resistant obsessive-compulsive disorder (OCD) patients can be successfully treated with Deep Brain Stimulation (DBS) which targets the anterior limb of the internal capsule (ALIC) and the nucleus accumbens (NA). Growing evidence suggests that in patients who respond to DBS, axonal fiber bundles surrounding the electrode are activated, but it is currently unknown which discrete pathways are critical for optimal benefit. Our aim was to identify axonal pathways mediating clinical effects of ALIC-NA DBS.Methods: We created computational models of ALIC-NA DBS to simulate the activation of fiber tracts and to identify connected cerebral regions. The pattern of activated axons and their cortical targets was investigated in six OCD patients who underwent ALIC-NA DBS. Results: Modulation of the right anterior middle frontal gyrus (dorsolateral prefrontal cortex) was associated with an excellent response. In contrast, non-responders showed high activation in the orbital part of the right inferior frontal gyrus (lateral orbitofrontal cortex/anterior ventrolateral prefrontal cortex). Factor analysis followed by step-wise linear regression indicated that YBOCS improvement was inversely associated with factors that were predominantly determined by gray matter activation results.Discussion: Our findings support the hypothesis that optimal therapeutic results are associated with the activation of distinct fiber pathways. This suggests that in DBS for OCD, focused stimulation of specific fiber pathways, which would allow for stimulation with lower amplitudes, may be superior to activation of a wide array of pathways, typically associated with higher stimulation amplitudes.