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Detection of neural signatures related to pathological behavioral states could enable adaptive deep brain stimulation (DBS), a potential strategy for improving efficacy of DBS for neurological and psychiatric disorders. This approach requires identifying neural biomarkers of relevant behavioral states, a task best performed in ecologically valid environments. Here, in human participants with obsessive-compulsive disorder (OCD) implanted with recording-capable DBS devices, we synchronized chronic ventral striatum local field potentials with relevant, disease-specific behaviors. We captured over 1,000 h of local field potentials in the clinic and at home during unstructured activity, as well as during DBS and exposure therapy. The wide range of symptom severity over which the data were captured allowed us to identify candidate neural biomarkers of OCD symptom intensity. This work demonstrates the feasibility and utility of capturing chronic intracranial electrophysiology during daily symptom fluctuations to enable neural biomarker identification, a prerequisite for future development of adaptive DBS for OCD and other psychiatric disorders. The identification of candidate neural biomarkers of obsessive-compulsive disorder symptom intensity in ecologically valid environments.

Abstract Deep brain stimulation (DBS) has emerged as a promising therapy for neuropsychiatric illnesses, including depression and obsessive-compulsive disorder, but has shown inconsistent results in prior clinical trials. We propose a shift away from the empirical paradigm for developing new DBS applications, traditionally based on testing brain targets with conventional stimulation paradigms. Instead, we propose a multimodal approach centered on an individualized intracranial investigation adapted from the epilepsy monitoring experience, which integrates comprehensive behavioral assessment, such as the Research Domain Criteria proposed by the National Institutes of Mental Health. In this paradigm-shifting approach, we combine readouts obtained from neurophysiology, behavioral assessments, and self-report during broad exploration of stimulation parameters and behavioral tasks to inform the selection of ideal DBS parameters. Such an approach not only provides a foundational understanding of dysfunctional circuits underlying symptom domains in neuropsychiatric conditions but also aims to identify generalizable principles that can ultimately enable individualization and optimization of therapy without intracranial monitoring.

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.

Despite having remarkable utility in treating movement disorders, the lack of understanding of the underlying mechanisms of high-frequency deep brain stimulation (DBS) is a main challenge in choosing personalized stimulation parameters. Here we investigate the modulations in local field potentials induced by electrical stimulation of the subthalamic nucleus (STN) at therapeutic and non-therapeutic frequencies in Parkinson’s disease patients undergoing DBS surgery. We find that therapeutic high-frequency stimulation (130–180 Hz) induces high-frequency oscillations (~300 Hz, HFO) similar to those observed with pharmacological treatment. Along with HFOs, we also observed evoked compound activity (ECA) after each stimulation pulse. While ECA was observed in both therapeutic and non-therapeutic (20 Hz) stimulation, the HFOs were induced only with therapeutic frequencies, and the associated ECA were significantly more resonant. The relative degree of enhancement in the HFO power was related to the interaction of stimulation pulse with the phase of ECA. We propose that high-frequency STN-DBS tunes the neural oscillations to their healthy/treated state, similar to pharmacological treatment, and the stimulation frequency to maximize these oscillations can be inferred from the phase of ECA waveforms of individual subjects. The induced HFOs can, therefore, be utilized as a marker of successful re-calibration of the dysfunctional circuit generating PD symptoms.Ozturk et al investigate the modulations in local field potentials induced by electrical stimulation of the subthalamic nucleus (STN) at therapeutic and nontherapeutic frequencies in Parkinson’s disease (PD) patients undergoing DBS surgery. They find evidence to suggest that high-frequency STN-DBS tunes the neural oscillations to their healthy/treated state, similar to pharmacological treatment and thus could serve to recalibrate the dysfunctional circuitry generating PD symptoms.

Bacterial infections account for a large proportion of zoonoses. Our current understanding of zoonotic spillover, however, is largely based on studies from viral systems. Small mammals such as rodents and their ectoparasites present a unique system for studying several bacterial pathogens and mapping their spillover pathways. Using Bartonella spp. (a Gram‐negative bacteria) as a model system within a rainforest human‐use landscape, we investigated (1) ecological correlates of Bartonella prevalence in small mammal hosts and (2) evolutionary relationships between Bartonella spp. and various hosts and ectoparasites to gain insight into pathogen movement pathways within ecological communities. We detected Bartonella in five out of eight small mammal species and in 86 (40.56%) out of 212 individuals, but prevalence varied widely among species (0%–75.8%). Seven of the ten ectoparasite species found on these small mammals were positive for Bartonella. Interestingly, while Bartonella genotypes (15) in small mammals were host‐specific, ectoparasites had nonspecific associations, suggesting the possibility for vector‐mediated cross‐species transmission. We also found that Bartonella prevalence in hosts was positively correlated with their aggregated ectoparasite loads, further emphasizing the crucial role that ectoparasites may play in these transmission pathways. Our cophylogenetic analysis and ancestral trait (host) reconstruction revealed incongruence between small mammal and Bartonella phylogenies, indicating historic host shifts and validating the potential for contemporary spillover events. We found that small mammal hosts in this fragmented landscape often move across habitat boundaries, creating a transmission pathway (via shared ectoparasites) to novel hosts, which may include synanthropic species like Rattus rattus. Our results highlight the necessity to disentangle the complex relationship among hosts, ectoparasites, and bacterial pathogens to understand the implications of undetected spillover events. This study focuses on Bartonella spp. (a Gram‐negative bacteria) in small mammals and their ectoparasites within a rainforest human‐use landscape. We found that a high proportion (40.56%) of the tested small mammals across five species and two sites carry Bartonella, with prevalence being positively correlated with aggregated ectoparasite load. Despite the occurrence of host‐specific genotypes, we observed incongruence in small mammal and Bartonella phylogenies, indicating historic host shifts within the community, and the potential for cross‐species transmissions in the future mediated by ectoparasites.

The mammalian target of rapamycin (mTOR) is a serine/threonine kinase that integrates metabolic and environmental signals to regulate cell growth and survival. In the central nervous system, mTOR plays a pivotal role in neuronal development, plasticity, and circuit homeostasis. In diffusely infiltrating gliomas, including glioblastomas, mTOR signaling is frequently dysregulated and contributes to malignant progression, therapeutic resistance, and metabolic adaptation. Beyond tumor-intrinsic effects, recent evidence reveals that gliomas actively reprogram peritumoral neurons via mTOR-dependent mechanisms, leading to synaptic remodeling, hyperexcitability, and neurological symptoms such as seizures and cognitive dysfunction. These results position mTOR as a central mediator of both oncogenesis and neurological dysfunction in diffusely infiltrating glioma. While clinical trials of mTOR inhibitors in gliomas have so far shown limited efficacy, emerging data suggest these agents may ameliorate tumor-associated neurological dysfunction. This review synthesizes current knowledge of mTOR signaling across tumor and neuronal compartments in diffusely infiltrating glioma and highlights its potential as a therapeutic target at the intersection of cancer biology and neuroscience.

Deep brain stimulation (DBS) is an emerging treatment strategy for severe, medication-refractory Tourette syndrome (TS). Thalamic (Cm-Pf) and pallidal (including globus pallidus interna, GPi) targets have been the most investigated. While the neurophysiological correlates of Parkinson's disease (PD) in the GPi and subthalamic nucleus (STN) are increasingly recognized, these patterns are not well characterized in other disease states. Recent findings indicate that the cross-frequency coupling (CFC) between beta band and high frequency oscillations (HFOs) within the STN in PD patients is pathologic. We recorded intraoperative local field potentials (LFPs) from the postero-ventrolateral GPi in three adult patients with TS at rest, during voluntary movements, and during tic activity and compared them to the intraoperative GPi-LFP activity recorded from four unmedicated PD patients at rest. In all PD patients, we noted excessive beta band activity (13-30 Hz) at rest which consistently modulated the amplitude of the co-existent HFOs observed between 200 and 400 Hz, indicating the presence of beta-HFO CFC. In all 3TS patients at rest, we observed theta band activity (4-7 Hz) and HFOs. Two patients had beta band activity, though at lower power than theta oscillations. Tic activity was associated with increased high frequency (200-400 Hz) and gamma band (35-200 Hz) activity. There was no beta-HFO CFC in TS patients at rest. However, CFC between the phase of 5-10 Hz band activity and the amplitude of HFOs was found in two TS patients. During tics, this shifted to CFC between the phase of beta band activity and the amplitude of HFOs in all subjects. To our knowledge this is the first study that shows that beta-HFO CFC exists in the GPi of TS patients during tics and at rest in PD patients, and suggests that this pattern might be specific to pathologic/involuntary movements. Furthermore, our findings suggest that during tics, resting state 5-10 Hz-HFO CFC shifts to beta-HFO CFC which can be used to trigger stimulation in a closed loop system when tics are present.

Birds and their habitats are threatened with extinction around the world. Regional assessments of the “State of Birds” are a vital means to prioritize data‐driven conservation action by informing national and global policy. Such evaluations have traditionally relied on data derived from extensive, long‐term, standardized surveys that require significant resources, limiting their feasibility to a few regions in the world. In the absence of such “structured” long‐term datasets, “semi‐structured” datasets have recently emerged as a promising alternative in other regions around the world. Semi‐structured data are generated and uploaded by birdwatchers to citizen science platforms such as eBird. Such data contain inherent biases because birdwatchers are not required to adhere to a fixed protocol. An evaluation of the status of birds from semi‐structured data is therefore a difficult task that requires careful curation of data and the use of robust statistical methods to reduce errors and biases. In this article, we present a methodology that was developed for this purpose and was applied to produce the comprehensive State of India's Birds (SoIB) 2023 report. SoIB 2023 assessed the status of 942 bird species in India by evaluating each species based on three metrics: (1) long‐term change, (2) current annual trend, and (3) distribution range size. We found evidence that 204 species have declined in the long term and that 142 species are in current decline. Birds that have vertebrate or invertebrate diets have declined most rapidly in the long term, whereas those that feed on fruits and nectar have been stable. Birds that require grasslands have declined more rapidly than those that require other habitats, indicating that grasslands are an important ecosystem to prioritize conservation in India. We classify 178 species as high conservation priority and present and discuss important insights about India's birds that can guide research and conservation action in the region. We hope that the detailed methodology described here can act as a blueprint to produce State of Birds assessments from semi‐structured citizen science datasets and springboard conservation action in many other regions where structured data are lacking but strong communities of birdwatchers exist.

The efficacy of deep brain stimulation (DBS) therapy in Parkinson's disease (PD) patients is highly dependent on the precise localization of the target structures such as subthalamic nucleus (STN). Most commonly, microelectrode single unit activity (SUA) recordings are performed to refine the target. This process is heavily experience based and can be technically challenging. Local field potentials (LFPs), representing the activity of a population of neurons, can be obtained from the same microelectrodes used for SUA recordings and allow flexible online processing with less computational complexity due to lower sampling rate requirements. Although LFPs have been shown to contain biomarkers capable of predicting patients' symptoms and differentiating various structures, their use in the localization of the STN in the clinical practice is not prevalent. Here we present, for the first time, a randomized and double-blinded pilot study with intraoperative online LFP processing in which we compare the clinical benefit from SUA- versus LFP-based implantation. Ten PD patients referred for bilateral STN-DBS were randomly implanted using either SUA or LFP guided targeting in each hemisphere. Although both SUA and LFP were recorded for each STN, the electrophysiologist was blinded to one at a time. Three months postoperatively, the patients were evaluated by a neurologist blinded to the intraoperative recordings to assess the performance of each modality. While SUA-based decisions relied on the visual and auditory inspection of the raw traces, LFP-based decisions were given through an online signal processing and machine learning pipeline. We found a dramatic agreement between LFP- and SUA-based localization (16/20 STNs) providing adequate clinical improvement (51.8% decrease in 3-month contralateral motor assessment scores), with LFP-guided implantation resulting in greater average improvement in the discordant cases (74.9%, = 3 STNs). The selected tracks were characterized by higher activity in beta (11-32 Hz) and high-frequency (200-400 Hz) bands ( < 0.01) of LFPs and stronger non-linear coupling between these bands ( < 0.05). Our pilot study shows equal or better clinical benefit with LFP-based targeting. Given the robustness of the electrode interface and lower computational cost, more centers can utilize LFP as a strategic feedback modality intraoperatively, in conjunction to the SUA-guided targeting.

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 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.