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Abstract The relative conservation of the influenza hemagglutinin (HA) stem compared to that of the immunodominant HA head makes the HA stem an attractive target for broadly protective influenza vaccines. Here we report the first-in-human, dose-escalation, open-label trial (NCT04579250) evaluating an unadjuvanted group 2 stabilized stem ferritin nanoparticle vaccine based on the H10 A/Jiangxi-Donghu/346/2013 influenza HA, H10ssF, in healthy adults. Participants received a single 20 mcg dose (n = 3) or two 60 mcg doses 16 weeks apart (n = 22). Vaccination with H10ssF was safe and well tolerated with only mild systemic and local reactogenicity reported. No serious adverse events occurred. Vaccination significantly increased homologous H10 HA stem binding and neutralizing antibodies at 2 weeks after both first and second vaccinations, and these responses remained above baseline at 40 weeks. Heterologous H3 and H7 binding antibodies also significantly increased after each vaccination and remained elevated throughout the study. These data indicate that the group 2 HA stem nanoparticle vaccine is safe and induces stem-directed binding and neutralizing antibodies.

Rachel Franklin,1 Sam Zorowitz,1 Andrew K Corse,1 Alik S Widge,2 Thilo Deckersbach1 1Division of Neurotherapeutics, Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Charlestown, 2Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, MA, USA Abstract: Bipolar disorder (BD) is a debilitating and difficult-to-treat psychiatric disease that presents a serious burden to patients’ lives as well as health care systems around the world. The essential diagnostic criterion for BD is episodes of mania or hypomania; however, the patients report that the majority of their time is spent in a depressive phase. Current treatment options for this component of BD have yet to achieve satisfactory remission rates. Lurasidone is a drug in the benzisothiazole class approved by the US Food and Drug Administration in June 2013 for the acute treatment of bipolar depression. Its pharmacological profile features high-affinity antagonism at D2, 5-HT2A, and 5-HT7 receptors; moderate-affinity antagonism at α2C-adrenergic receptors; low- to very low-affinity antagonism at α1A-adrenergic, α2A-adrenergic, H1, M1, and 5-HT2C receptors; and high-affinity partial agonism at 5-HT1A. Preliminary findings from two recent double-blinded clinical trials suggest that lurasidone is efficacious in treating bipolar I depression, with clinical effects manifesting as early as the first 2–3 weeks of treatment (as measured by the Montgomery–Åsberg Depression Rating Scale and Clinical Global Impressions Scale for use in bipolar illness). Its therapeutic benefit appears to be comparable to the current US Food and Drug Administration-indicated treatments: quetiapine and olanzapine–fluoxetine, according to a measure of effect size known as number needed to treat. These studies reported relatively limited extrapyramidal and metabolic side effects as a result of treatment with lurasidone, with the most common side effect being nausea. Safety data drawn from these studies, as well as a more extensive body of schizophrenia research, indicate that in comparison with other atypical antipsychotics, treatment with lurasidone is less likely to result in metabolic side effects such as weight gain or disturbances of serum glucose or lipid levels. Lurasidone holds clinical potential as a novel, efficacious pharmacological treatment for bipolar depression. However, current data on its use for the treatment of BD are limited, and more extensive research, both longer in duration as well as independently conducted, is needed. Keywords: lurasidone, bipolar depression, bipolar disorder, atypical antipsychotic

Since the introduction of the first antidepressant in the 1950s, biological treatments for unipolar depressive disorders have largely focused on altering monoaminergic neurotransmission, with varying degrees of success. In the [...]

Background: A developing literature suggests that transcranial magnetic stimulation (TMS) can target anhedonia and suicidal ideation (SI), core symptoms of treatment-resistant depression (TRD). This present naturalistic study extends the existing literature by investigating the connection between changes in anhedonia and suicidal ideation (SI) related to transcranial magnetic stimulation (TMS), independent of any overall changes in depression. Methods: Pre and post treatment PHQ-9 and IDS-SR data were collected from 181 TRD patients who received dorsolateral prefrontal cortex ( dlPFC) TMS using the Figure-8 or H1-coil. Changes in overall depression symptoms, anhedonia, and SI were analyzed using chi square tests, repeated measure ANOVAS, and linear regression for repeated measures. Results: TMS yielded changes in overall depression symptoms (PHQ-9 Cohen’s d = 1.02; IDS-SR Cohen’s d = 1.05), with 23.9 % and 41.7 % of patients experiencing response as measured by IDS-SR and PHQ-9, respectively. TMS treatment was also associated with large changes in both anhedonia (d = 1.03) and SI (d = 0.88), which were similar in magnitude to changes in all other depression symptoms (d = 0.97). Importantly, changes in anhedonia predicted changes in SI, even after controlling for baseline depression severity and change in other depression symptoms. Limitations: The lack of a control arm and a neuroimaging measure temper mechanistic conclusion. Conclusion: Our results reinforce the effectiveness of TMS in TRD and provide new evidence that anhedonia and SI may belong to a broader symptom cluster potentially undergirded by a shared circuitry accessible to dlPFC TMS.

Extracting meaningful information from high-dimensional data poses a formidable modeling challenge, particularly when the data is obscured by noise or represented through different modalities. This research proposes a novel non-parametric modeling approach, leveraging the Gaussian process (GP), to characterize high-dimensional data by mapping it to a latent low-dimensional manifold. This model, named the latent discriminative generative decoder (LDGD), employs both the data and associated labels in the manifold discovery process. A Bayesian solution is derived to infer the latent variables, allowing LDGD to effectively capture inherent stochasticity in the data. Applications of LDGD are demonstrated on both synthetic and benchmark datasets. Not only does LDGD infer the manifold accurately, but its accuracy in predicting data points’ labels surpasses state-of-the-art approaches. In the development of LDGD, inducing points are incorporated to reduce the computational complexity of Gaussian processes for large datasets, enabling batch training for enhanced efficient processing and scalability. Additionally, we show that LDGD can robustly infer manifold and precisely predict labels for scenarios in which data size is limited, demonstrating its capability to characterize high-dimensional data with limited samples efficiently. These collective attributes highlight the importance of developing non-parametric modeling approaches to analyze high-dimensional data.

Background: Fear overgeneralization is a promising pathogenic mechanism of clinical anxiety. A dominant model posits that hippocampal pattern separation failures drive overgeneralization. Hippocampal network–targeted transcranial magnetic stimulation (HNT-TMS) has been shown to strengthen hippocampal-dependent learning/memory processes. However, no study has examined whether HNT-TMS can alter fear learning/memory. Methods: Continuous theta burst stimulation was delivered to individualized left posterior parietal stimulation sites derived via seed-based connectivity, precision functional mapping, and electric field modeling methods. A vertex control site was also stimulated in a within-participant, randomized controlled design. Continuous theta burst stimulation was delivered prior to 2 visual discrimination tasks (1 fear based, 1 neutral). Multilevel models were used to model and test data. Participants were undergraduates with posttraumatic stress symptoms (final n = 25). Results: Main analyses did not indicate that HNT-TMS strengthened discrimination. However, multilevel interaction analyses revealed that HNT-TMS strengthened fear discrimination in participants with lower fear sensitization (indexed by responses to a control stimulus with no similarity to the conditioned fear cue) across multiple indices (anxiety ratings: β = 0.10, 95% CI, 0.04 to 0.17, p = .001; risk ratings: β = 0.07, 95% CI, 0.00 to 0.13, p = .037). Conclusions: Overgeneralization is an associative process that reflects deficient discrimination of the fear cue from similar cues. In contrast, sensitization reflects nonassociative responding unrelated to fear cue similarity. Our results suggest that HNT-TMS may selectively sharpen fear discrimination when associative response patterns, which putatively implicate the hippocampus, are more strongly engaged.

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.

Background: Electrical neuromodulation via direct electrical stimulation (DES) is an increasingly common therapy for a wide variety of neuropsychiatric diseases. Unfortunately, therapeutic efficacy is inconsistent, likely due to our limited understanding of the relationship between the massive stimulation parameter space and brain tissue responses. Objective: To better understand how different parameters induce varied neural responses, we systematically examined single pulse-induced cortico-cortico evoked potentials (CCEP) as a function of stimulation amplitude, duration, brain region, and whether grey or white matter was stimulated. Methods: We measured voltage peak amplitudes and area under the curve (AUC) of intracranially recorded stimulation responses as a function of distance from the stimulation site, pulse width, current injected, location relative to grey and white matter, and brain region stimulated (N = 52, n = 719 stimulation sites). Results: Increasing stimulation pulse width increased responses near the stimulation location. Increasing stimulation amplitude (current) increased both evoked amplitudes and AUC nonlinearly. Locally (15 mm), white matter stimulation consistently produced larger responses than stimulation in or near grey matter. The stimulation location-response curves followed different trends for cingulate, lateral frontal, and lateral temporal cortical stimulation. Conclusion: These results demonstrate that a stronger local response may require stimulation in the grey-white boundary while stimulation in the white matter could be needed for network activation. Thus, stimulation parameters tailored for a specific anatomical-functional outcome may be key to advancing neuromodulatory therapy.

Objective: In this review, the authors update the 2018 position statement of the American Psychiatric Association Council of Research Workgroup on Biomarkers and Novel Treatments on pharmacogenomic (PGx) tools for treatment selection in depression. Methods: The literature was reviewed for new clinical trials and meta-analyses, published from 2017 to 2022, of studies using PGx tools for treatment selection in depression. The blinding and control conditions, as well as primary and secondary outcomes and post hoc analyses, were summarized. Results: Eleven new clinical trials and five meta-analyses were identified; all studies had primary outcome measures related to speed or efficacy of treatment response. Three trials (27%) demonstrated efficacy on the primary outcome measure with statistical significance; the three studies used different PGx tools; one study was open-label and the other two were small single-blind trials. Five trials (45%) did not detect efficacy with statistical significance on either primary or secondary outcome measures. Only one trial (9%) used adverse events as a primary outcome measure. All studies had significant limitations; for example, none adopted a fully blinded study design, only two studies attempted to blind the treating clinician, and none incorporated measures to estimate the effectiveness of the blinds or the influence of lack of blinding on the study results. Conclusions: The addition of these new data do not alter the recommendations of the 2018 report, or the advice of the U.S. Food and Drug Administration, that the evidence does not support the use of currently available combinatorial PGx tools for treatment selection in major depressive disorder. Priority efforts for future studies and the development and testing of effective tools include fully blinded study designs, inclusion of promising genetic variants not currently included in any commercially available tests, and investigation of other uses of pharmacogenomics, such as estimating the likelihood of rare adverse drug effects, rather than increasing the speed or magnitude of drug response. [ABSTRACT FROM AUTHOR]

Brain rhythms have been proposed to facilitate brain function, with an especially important role attributed to the phase of low-frequency rhythms. Understanding the role of phase in neural function requires interventions that perturb neural activity at a target phase, necessitating estimation of phase in real-time. Current methods for real-time phase estimation rely on bandpass filtering, which assumes narrowband signals and couples the signal and noise in the phase estimate, adding noise to the phase and impairing detections of relationships between phase and behavior. To address this, we propose a state space phase estimator for real-time tracking of phase. By tracking the analytic signal as a latent state, this framework avoids the requirement of bandpass filtering, separately models the signal and the noise, accounts for rhythmic confounds, and provides credible intervals for the phase estimate. We demonstrate in simulations that the state space phase estimator outperforms current state-of-the-art real-time methods in the contexts of common confounds such as broadband rhythms, phase resets, and co-occurring rhythms. Finally, we show applications of this approach to in vivo data. The method is available as a ready-to-use plug-in for the Open Ephys acquisition system, making it widely available for use in experiments.

Introduction Sleep disturbance specifically insomnia, non-restorative sleep, and hypersomnia are common symptoms of major depressive disorder (MDD). As it alleviates major depressive disorder, transcranial magnetic stimulation (TMS) may improve associated sleep disturbances, and may also have inherent sedating or activating properties. Objectives To examine the impact of TMS on sleep disturbances in adults with treatment resistant depression in a clinical setting, we retrospectively reviewed de-identified data from naturalistically-treated MDD patients undergoing an initial acute course of TMS therapy at St.Louis Park MinCEP Clinic. Methods Adults with treatment-resistant depression received daily TMS treatments. 9-item Patient Health Questionnaire (PHQ-9) total scores were used to calculate % change at endpoint (relative to pretreatment baseline); response on both measures was defined as 50% reduction in scores, with remission defined as a final total score 4 on the PHQ-9. Insomnia was measured with a 3-item subscale of the Inventory of Depressive Symptomatology Self Report (IDS-SR). Hypersomnia was measured with a single IDS-SR item. Pairwise comparisons were performed using Student’s T-test. Categorical variables were compared using Fisher’s Exact test. Continuous outcome measures were tested with an analysis of covariance, using baseline PHQ-9 score as a fixed effect covariate. Results TMS appears to have differential modulatory effects on insomnia and hypersomnia in adults with treatment resistant depression. Conclusions These results may provide the basis for further investigation into therapeutic applications of TMS in addressing sleep disturbances in treatment-resistant depression. Measures that separate hypersomnia and insomnia should be implemented in future work addressing effects of TMS in treatment-resistant depression. Disclosure No significant relationships.

Targeted interrogation of brain networks through invasive brain stimulation has become an increasingly important research tool as well as therapeutic modality. The majority of work with this emerging capability has been focused on open-loop approaches. Closed-loop techniques, however, could improve neuromodulatory therapies and research investigations by optimizing stimulation approaches using neurally informed, personalized targets. Implementing closed-loop systems is challenging particularly with regard to applying consistent strategies considering inter-individual variability. In particular, during intracranial epilepsy monitoring, where much of this research is currently progressing, electrodes are implanted exclusively for clinical reasons. Thus, detection and stimulation sites must be participant- and task-specific. The system must run in parallel with clinical systems, integrate seamlessly with existing setups, and ensure safety features are in place. In other words, a robust, yet flexible platform is required to perform different tests with a single participant and to comply with clinical requirements.In order to investigate closed-loop stimulation for research and therapeutic use, we developed a Closed-Loop System for Electrical Stimulation (CLoSES) that computes neural features which are then used in a decision algorithm to trigger stimulation in near real-time. To summarize CLoSES, intracranial electroencephalography (iEEG) signals are acquired, band-pass filtered, and local and network features are continuously computed. If target features are detected (e.g. above a preset threshold for a certain duration), stimulation is triggered. Not only could the system trigger stimulation while detecting real-time neural features, but we incorporated a pipeline wherein we used an encoder/decoder model to estimate a hidden cognitive state from the neural features.CLoSES provides a flexible platform to implement a variety of closed-loop experimental paradigms in humans. CLoSES has been successfully used with twelve patients implanted with depth electrodes in the epilepsy monitoring unit. During cognitive tasks (N=5), stimulation in closed loop modified a cognitive hidden state on a trial by trial basis. Sleep spindle oscillations (N=6) and sharp transient epileptic activity (N=9) were detected in near real-time, and stimulation was applied during the event or at specified delays (N=3). In addition, we measured the capabilities of the CLoSES system. Total latency was related to the characteristics of the event being detected, with tens of milliseconds for epileptic activity and hundreds of milliseconds for spindle detection. Stepwise latency, the actual duration of each continuous step, was within the specified fixed-step duration and increased linearly with the number of channels and features.We anticipate that probing neural dynamics and interaction between brain states and stimulation responses with CLoSES will lead to novel insights into the mechanism of normal and pathological brain activity, the discovery and evaluation of potential electrographic biomarkers of neurological and psychiatric disorders, and the development and testing of patient-specific stimulation targets and control signals before implanting a therapeutic device.

Psychiatric disorders are increasingly understood as dysfunctions of hyper- or hypoconnectivity in distributed brain circuits. A prototypical example is obsessive compulsive disorder (OCD), which has been repeatedly linked to hyper-connectivity of cortico-striatal-thalamo-cortical (CSTC) loops. Deep brain stimulation (DBS) and lesions of CSTC structures have shown promise for treating both OCD and related disorders involving over-expression of automatic/habitual behaviors. Physiologically, we propose that this CSTC hyper-connectivity may be reflected in high synchrony of neural firing between loop structures, which could be measured as coherent oscillations in the local field potential (LFP). Here we report the results from the pilot patient in an Early Feasibility study (https://clinicaltrials.gov/ct2/show/NCT03184454) in which we use the Medtronic Activa PC+ S device to simultaneously record and stimulate in the supplementary motor area (SMA) and ventral capsule/ventral striatum (VC/VS). We hypothesized that frequency-mismatched stimulation should disrupt coherence and reduce compulsive symptoms. The patient reported subjective improvement in OCD symptoms and showed evidence of improved cognitive control with the addition of cortical stimulation, but these changes were not reflected in primary rating scales specific to OCD and depression, or during blinded cortical stimulation. This subjective improvement was correlated with increased SMA and VC/VS coherence in the alpha, beta, and gamma bands, signals which persisted after correcting for stimulation artifacts. We discuss the implications of this research, and propose future directions for research in network modulation in OCD and more broadly across psychiatric disorders.