Hasil untuk "Neurosciences. Biological psychiatry. Neuropsychiatry"

Stephanie Mehl, Christopher Hautmann, Björn Schlier et al.

Abstract Psychological interventions for delusions may be enhanced by targeting their presumed causal factors. An emotion-oriented variant of cognitive behavioral therapy for delusions (CBTd-E), designed to target affect regulation and maladaptive schemata, was evaluated for its effect on delusions. A single-blind, multicenter, randomized, waitlist-controlled trial was conducted in three German outpatient clinics. Ninety-four patients with psychotic disorders and persistent delusions were randomized to 25 individual sessions of CBTd-E over 6 months (n = 47) or waitlist (n = 47). CBTd-E included two modules designed to improve affect regulation and maladaptive schemata. Assessments were performed at baseline (T1), three months (T2), and six months (T3). Regression-based analysis of covariance at T3 in the intent-to-treat sample indicated no significant benefit for the CBT-E group in the primary outcome (Psychotic Symptom Rating Scale delusions subscale, d = -0.45 [CI: 0.36; -1.26]). Regarding secondary outcomes, a significant effect favoring CBTd-E was observed in general psychopathology (d = -0.56), but no effects on positive and negative symptoms, depression, general and social functioning, or antipsychotic dosage. Regarding the proposed target mechanisms, we found improved cognitive reappraisal (d = 0.59), worrying (d = -0.52), quality of sleep (d = -0.49), and self-esteem (d = 0.36). Despite its effect on the suggested target mechanisms, affect regulation and maladaptive schemata, and on general psychopathology, this emotion-focused variant of CBT did not show an effect on delusions. A possible avenue to achieve stronger effects on delusions is to personalize the modularized interventions. Trial registration: Clinicaltrials.gov Identifier: NCT02787135

Jing Jin, Yun Wang, Sixiang Liang et al.

Objective: Repetitive transcranial magnetic stimulation (rTMS) has been shown to alleviate depressive and anxiety symptoms in patients with major depressive disorder (MDD), typically by targeting the dorsolateral (DLPFC) or dorsomedial prefrontal cortex (DMPFC). Based on a pre-registered randomized controlled trial, this study presents an exploratory neuroimaging analysis investigating the impact of rTMS targeting the DLPFC versus the DMPFC on functional connectivity with the default mode network (DMN) and frontal-parietal network (FPN) in patients with MDD. Methods: Sixty-four MDD patients were randomly assigned to DLPFC-rTMS (n = 36) or DMPFC-rTMS (n = 28) groups for a 21-day intervention. Symptoms were evaluated with Hamilton Depression Rating Scale (HAMD) and Hamilton Anxiety Rating Scale (HAMA). Changes in individualized functional connectivity (inFC) between individualized targets and DMN/FPN were assessed and correlated with symptom improvements. As a control analysis, FC was evaluated based on the group-based seeds of DLPFC or DMPFC. Additionally, symptom-specific circuit map comparisons were conducted. Results: Both groups showed symptom improvements and changes in inFC with the DMN and FPN, but the specific connectivity profiles differ. In the DMN, the DLPFC-rTMS group showed decreased negative connectivity between left DLPFC and precuneus (t = -2.39, p = 0.022), while the DMPFC-rTMS group showed increased positive inFC between DMPFC and precuneus (t = -2.78, p = 0.01, FDR adjusted p = 0.034) and PCC (t = -3.15, p = 0.004, FDR adjusted p = 0.028). In the FPN, the DLPFC group showed decreased negative inFC with medial superior frontal gyrus (t = -2.35, p = 0.024) and decreased positive inFC with inferior parietal lobule (t = 2.3, p = 0.028). The DMPFC group showed increased positive connectivity with inferior frontal gyrus (t = -3.65, p = 0.001, FDR adjusted p = 0.019) and su pplementary motor area (t = -2.24, p = 0.033), and decreased negative connectivity with middle cingulate cortex (t = 2.27, p = 0.032). Canonical correlation analysis revealed a strong association between inFC changes and depression symptom improvement in the DMPFC-rTMS group (r = 0.57). Group seed-based FC changes were limited to the FPN and correlated with depressive improvement in the DLPFC-rTMS group (r = 0.52). Symptom-specific circuit maps linked to depression and anxiety were consistent across targets. Conclusion: Both DLPFC and DMPFC rTMS alleviate depressive and anxiety symptoms, displaying similar overall circuit patterns but distinct connectivity changes specific to their targets.

Changze Lv, Jingwen Xu, Yiyang Lu et al.

Backpropagation is the foundational algorithm for training neural networks and a key driver of deep learning's success. However, its biological plausibility has been challenged due to three primary limitations: weight symmetry, reliance on global error signals, and the dual-phase nature of training, as highlighted by the existing literature. Although various alternative learning approaches have been proposed to address these issues, most either fail to satisfy all three criteria simultaneously or yield suboptimal results. Inspired by the dynamics and plasticity of pyramidal neurons, we propose Dendritic Localized Learning (DLL), a novel learning algorithm designed to overcome these challenges. Extensive empirical experiments demonstrate that DLL satisfies all three criteria of biological plausibility while achieving state-of-the-art performance among algorithms that meet these requirements. Furthermore, DLL exhibits strong generalization across a range of architectures, including MLPs, CNNs, and RNNs. These results, benchmarked against existing biologically plausible learning algorithms, offer valuable empirical insights for future research. We hope this study can inspire the development of new biologically plausible algorithms for training multilayer networks and advancing progress in both neuroscience and machine learning. Our code is available at https://github.com/Lvchangze/Dendritic-Localized-Learning.

Joshua B. Fernandes, Hyeongjoo Row, Kranthi K. Mandadapu et al.

Electrochemical phenomena in biology often unfold in confined geometries where micrometer- to millimeter-scale domains coexist with nanometer-scale interfacial diffuse charge layers. We analyze a model lipid membrane-electrolyte system where an ion channel-like current flows across the membrane while parallel electrodes simultaneously apply a step voltage, emulating an extrinsic electric field. Matched asymptotic expansions of the Poisson-Nernst-Planck equations show that, under physiological conditions, the diffuse charge layers rapidly reach a quasi-steady state, and the bulk electrolyte remains electroneutral. As a result, all free charge is confined to the nanometer-scale screening layers at the membrane and electrode interfaces. The bulk electric potential satisfies Laplace's equation, and is dynamically coupled to the interfacial layers through time-dependent boundary conditions. This multiscale coupling partitions the space-time response into distinct regimes. At sufficiently long times, we show that the system can be represented by an equivalent circuit analogous to those used in classical cable theory. We derive closed-form expressions of the transmembrane potential within each regime, and verify them against nonlinear numerical simulations. Our results show how electrode-induced screening and confinement effects influence the electrochemical response over multiple length and time scales in biological systems.

Sylvain Fontaine

Neuroscience and AI have an intertwined history, largely relayed in the literature of both fields. In recent years, due to the engineering orientations of AI research and the monopoly of industry for its large-scale applications, the mutual expansion of neuroscience and AI in fundamental research seems challenged. In this paper, we bring some empirical evidences that, on the contrary, AI and neuroscience are continuing to grow together, but with a pronounced interest in the fields of study related to neurodegenerative diseases since the 1990s. With a temporal knowledge cartography of neuroscience drawn with advanced document embedding techniques, we draw the dynamical shaping of the discipline since the 1970s and identified the conceptual articulation of AI with this particular subfield mentioned before. However, a further analysis of the underlying citation network of the studied corpus shows that the produced AI technologies remain confined in the different subfields and are not transferred from one subfield to another. This invites us to discuss the genericity capability of AI in the context of an intradisciplinary development, especially in the diffusion of its associated metrology.

Ke Liu, Shuaike Shen, Hao Chen

The paradigm of large language models in natural language processing (NLP) has also shown promise in modeling biological languages, including proteins, RNA, and DNA. Both the auto-regressive generation paradigm and evaluation metrics have been transferred from NLP to biological sequence modeling. However, the intrinsic structural correlations in natural and biological languages differ fundamentally. Therefore, we revisit the notion of language in biological systems to better understand how NLP successes can be effectively translated to biological domains. By treating the 3D structure of biomolecules as the semantic content of a sentence and accounting for the strong correlations between residues or bases, we highlight the importance of structural evaluation and demonstrate the applicability of the auto-regressive paradigm in biological language modeling. Code can be found at \href{https://github.com/zjuKeLiu/RiFold}{github.com/zjuKeLiu/RiFold}

Bandita Abhijita, Jilisha Gnanadhas, Sujita Kumar Kar et al.

Rabah Dabouz, Pénélope Abram, Jose Carlos Rivera et al.

Abstract ‘Wet’ age-related macular degeneration (AMD) is characterized by pathologic choroidal neovascularization (CNV) that destroys central vision. Abundant evidence points to inflammation and immune cell dysfunction in the progression of CNV in AMD. Mast cells are resident immune cells that control the inflammatory response. Mast cells accumulate and degranulate in the choroid of patients with AMD, suggesting they play a role in CNV. Activated mast cells secrete various biologically active mediators, including inflammatory cytokines and proteolytic enzymes such as tryptase. We investigated the role of mast cells in AMD using a model of CNV. Conditioned media from activated mast cells exerts proangiogenic effects on choroidal endothelial cells and choroidal explants. Laser-induced CNV in vivo was markedly attenuated in mice genetically depleted of mast cells (KitW−sh/W−sh) and in wild-type mice treated with mast cell stabilizer, ketotifen fumarate. Tryptase was found to elicit pronounced choroidal endothelial cell sprouting, migration and tubulogenesis; while tryptase inhibition diminished CNV. Transcriptomic analysis of laser-treated RPE/choroid complex revealed collagen catabolism and extracellular matrix (ECM) reorganization as significant events correlated in clusters of mast cell activation. Consistent with these analyses, compared to wildtype mice choroids of laser-treated mast cell-deficient mice displayed less ECM remodelling evaluated using collagen hybridizing peptide tissue binding. Findings herein provide strong support for mast cells as key players in the progression of pathologic choroidal angiogenesis and as potential therapeutic targets to prevent pathological neovascularization in ‘wet’ AMD.

Auob Rustamzadeh, Nader Sadigh, Zahra Vahabi et al.

Purpose: The production/excretion rate of Amyloid-β (Aβ) is the basis of the plaque burden in alzheimer's disease (AD), which depends on both central and peripheral clearance. In this study, the effect of silymarin and rosuvastatin on serum markers and clinical outcomes in dyslipidemic AD patients was investigated. Methods: Participants (n=36) were randomized to silymarin (140 mg), placebo, and rosuvastatin 10 mg orally three times a day for 6 months. Serum collection and clinical outcome tests were performed at baseline and after completion of treatment. Lipid profile markers, oxidative stress markers, Aβ1–42/Aβ1–40 ratio, and Soluble Low-density lipoprotein receptor-Related Protein-1 (sLRP1)/Soluble Receptor for Advanced Glycation End Products (sRAGE) ratio were measured. Results: There was a statistically significant increase in Δ-high density lipoprotein (ΔHDL) between silymarin and placebo (P<0.000) and also between rosuvastatin and placebo (p=0.044). The level of Δ-triglycerides (ΔTG) in the silymarin group has a significant decrease compared to both the placebo and the rosuvastatin group (p<0.000 and p=0.036, respectively). The Δ-superoxide dismutase (ΔSOD) level in the silymarin group compared to placebo and rosuvastatin had a significant increase (p<0.000 and p=0.008, respectively). The ΔAβ1–42/Aβ1–40 in the silymarin group compared to both the placebo and rosuvastatin groups had a significant increase (p<0.05). There was an inverse relationship between ΔTG and ΔAβ1–42/Aβ1–40 (p=-0.493 and p=0.004). ΔAβ1–42/Aβ1–40 has a direct statistical relationship with ΔSOD marker (p=0.388 and p=0.031). Also, there was a direct correlation between the level of ΔAβ1–42/Aβ1–40 and ΔsLRP1/sRAGE (p=0.491 and p=0.005). Conclusion: Our study showed the relationship between plasma lipids, especially ΔTG and ΔHDL, with ΔAβ1–42/Aβ1–40 in dyslipidemic AD patients, and modulation of these lipid factors can be used to monitor the response to treatments.

C. García Sánchez, I. Martín Galledo, A. Guerra Huelves et al.

T. Insel

Esther-Sevil Eigl, Laura Krystin Urban-Ferreira, Manuel Schabus et al.

BackgroundApproximately one-third of the healthy population suffer from sleep problems, but only a small proportion of those affected receive professional help. Therefore, there is an urgent need for easily accessible, affordable, and efficacious sleep interventions.ObjectiveA randomized controlled study was conducted to investigate the efficacy of a low-threshold sleep intervention consisting of either (i) sleep data feedback plus sleep education or (ii) sleep data feedback alone in comparison with (iii) no intervention.Material and methodsA total of 100 employees of the University of Salzburg (age: 39.51 ± 11.43 years, range: 22–62 years) were randomly assigned to one of the three groups. During the 2-week study period, objective sleep parameters were assessed via actigraphy. In addition, an online questionnaire and a daily digital diary were used to record subjective sleep parameters, work-related factors, as well as mood and well-being. After 1 week, a personal appointment was conducted with participants of both experimental group 1 (EG1) and experimental group 2 (EG2). While the EG2 only received feedback about their sleep data from week 1, the EG1 additionally received a 45-min sleep education intervention containing sleep hygiene rules and recommendations regarding stimulus control. A waiting-list control group (CG) did not receive any feedback until the end of the study.ResultsResults indicate positive effects on sleep and well-being following sleep monitoring over the course of 2 weeks and minimal intervention with a single in-person appointment including sleep data feedback. Improvements are seen in sleep quality, mood, vitality, and actigraphy-measured sleep efficiency (SE; EG1), as well as in well-being and sleep onset latency (SOL) in EG2. The inactive CG did not improve in any parameter.ConclusionResults suggest small and beneficial effects on sleep and well-being in people being continuously monitored and receiving (actigraphy-based) sleep feedback when paired with a single-time personal intervention.

Ronnie Baer, Ronit Feingold-Polak, Ronit Feingold-Polak et al.

Galen Pogoncheff, Jacob Granley, Michael Beyeler

Convolutional neural networks (CNNs) have recently emerged as promising models of the ventral visual stream, despite their lack of biological specificity. While current state-of-the-art models of the primary visual cortex (V1) have surfaced from training with adversarial examples and extensively augmented data, these models are still unable to explain key neural properties observed in V1 that arise from biological circuitry. To address this gap, we systematically incorporated neuroscience-derived architectural components into CNNs to identify a set of mechanisms and architectures that comprehensively explain neural activity in V1. We show drastic improvements in model-V1 alignment driven by the integration of architectural components that simulate center-surround antagonism, local receptive fields, tuned normalization, and cortical magnification. Upon enhancing task-driven CNNs with a collection of these specialized components, we uncover models with latent representations that yield state-of-the-art explanation of V1 neural activity and tuning properties. Our results highlight an important advancement in the field of NeuroAI, as we systematically establish a set of architectural components that contribute to unprecedented explanation of V1. The neuroscience insights that could be gleaned from increasingly accurate in-silico models of the brain have the potential to greatly advance the fields of both neuroscience and artificial intelligence.

Manpreet K. Singh, Akua F. Nimarko, J. Bruno et al.

Social isolation and conflict due to structural racism may result in human suffering and loneliness across the lifespan. Given the rising prevalence of these problems in America, combined with disruptions experienced during the COVID-19 pandemic, the neurobiology of affiliative behaviors may offer practical solutions to the pressing challenges associated with structural racism. Controlled experiments across species demonstrate that social connections are critical to survival, although strengthening individual resilience is insufficient to address the magnitude and impact of structural racism. In contrast, the multi-level construct of social resilience, defined by the power of groups to cultivate, engage in, and sustain positive relationships that endure and recuperate from social adversities, offers unique insights that may have greater impact, reach, and durability than individual-level interventions. Here, we review the putative social resilience-enhancing interventions and, when available, their biological mediators, with the hope to stimulate discovery of novel approaches to mitigate structural racism. We will first explore the social neuroscience principles underlying psychotherapy and other psychiatric interventions. Then, we will explore translational efforts across species to tailor treatments that increase social resilience, with context and cultural sensitivity in mind. Finally, we will conclude with some practical future directions for understudied areas that may be essential for progress in biological psychiatry, including ethical ways to increase representation in research and developing social paradigms that inform dynamics toward or away from socially resilient outcomes.

Ana Fernández Rodríguez

Bunty Sharma, Deeksha Pal, Ujjawal Sharma et al.

Mitochondria provide neurons not only energy as ATP to keep them growing, proliferating and developing, but they also control apoptosis. Due to their high bioenergetic demand, neurons which are highly specific terminally differentiated cells, essentially depend on mitochondria. Defective mitochondrial function is thus related to numerous age-linked neurodegenerative ailments like Alzheimer’s disease (AD), in which the build-up of impaired and malfunctioning mitochondria has been identified as a primary sign, paying to disease development. Mitophagy, selective autophagy, is a key mitochondrial quality control system that helps neurons to stay healthy and functional by removing undesired and damaged mitochondria. Dysfunctional mitochondria and dysregulated mitophagy have been closely associated with the onset of ADs. Various proteins associated with mitophagy were found to be altered in AD. Therapeutic strategies focusing on the restoration of mitophagy capabilities could be utilized to strike the development of AD pathogenesis. We summarize the mechanism and role of mitophagy in the onset and advancement of AD, in the quality control mechanism of mitochondria, the consequences of dysfunctional mitophagy in AD, and potential therapeutic approaches involving mitophagy modulation in AD. To develop new therapeutic methods, a better knowledge of the function of mitophagy in the pathophysiology of AD is required.

Clara Weber, Clara Weber, Virna Monero Flores et al.

Background: Previous research indicates that the physical environment of healthcare facilities plays an important role in the health, well-being, and recovery outcomes of patients. However, prior works on mental healthcare facilities have incorporated physical environment effects from general healthcare settings and patient groups, which cannot be readily transferred to mental healthcare settings or its patients. There appears to be a specific need for evidence synthesis of physical environmental effects in mental healthcare settings by psychopathology.Purpose: This review evaluates the state (in terms of extent, nature and quality) of the current empirical evidence of physical environmental on mental health, well-being, and recovery outcomes in mental healthcare inpatients by psychopathology.Method: A systematic review (PRISMA guidelines) was performed of studies published in English, German, Dutch, Swedish, and Spanish, of all available years until September 2020, searched in Cochrane, Ovid Index, PsycINFO, PubMed, and Web of Science and identified through extensive hand-picking. Inclusion criteria were: Adult patients being treated for mental ill-health (common mental health and mood disorders, Cochrane frame); inpatient mental health care facilities; specifications of the physical and socio-physical environment (e.g., design features, ambient conditions, privacy); all types of empirical study designs. Quality assessment and data synthesis were undertaken.Results: The search retrieved 1,068 titles of which 26 met the inclusion criteria. Findings suggest that there is only indicative evidence of the impact of the physical healthcare environment on patients' mental health, well-being, and recovery outcomes. There is significant lack of pathology-specific evidence. Methodological shortcomings and empirical scarcity account for the poor evidence.Conclusion: This review highlights the need for more research using advanced study designs.

Sungsam Kang, Renjie Zhou, Marten Brelen et al.

Optical diffraction tomography (ODT) has emerged as a powerful label-free three-dimensional (3D) bioimaging techniques for observing living cells and thin tissue layers. We report a new reflection-mode ODT (rODT) method for imaging thick biological specimens with 500 nm lateral resolution and 1 μm axial resolution. In rODT, multiple scattering background is rejected through spatio-temporal gating provided by dynamic speckle-field interferometry, while depth-resolved refractive index maps are reconstructed by developing a comprehensive inverse scattering model that also considers specimen-induced aberration. Benefiting from the high-resolution and full-field quantitative imaging capabilities of rODT, we succeeded in imaging red blood cells and quantifying their membrane fluctuations behind a turbid sample with a thickness of 2.8 scattering mean-free-paths. We further realized volumetric imaging of cornea inside an ex vivo rat eye and quantified its optical properties, including mapping the topography of Dua's and Descemet's membrane surfaces on the nanometer scale.

K. Aryutova, D. Stoyanov, S. Kandilarova et al.

Psychoses and affective disorders are severe mental illnesses with a considerable negative effect on an individual and global scale. They are among the most damaging and socially significant diseases, which contribute to permanent disabilities for the patients. The aim of this review is to analyse the capacity of neuroscientific methods as tools to reform psychiatry into a biologically valid medical discipline. Furthermore, it will focus on the application of the translational approach towards the diagnostic and therapeutic processes, as well as monitoring of treatment response by using valid biomarkers and psychometric instruments. By combining translational neuroscience with the latest psychopharmacology advances clinicians might be able to provide better quality of precision and individualized medical care for their patients. We visualise a reality in which neuroimaging methods will modify standard clinical evaluation of neuropsychiatric disorders, leading to a biologically valid diagnosis, monitoring and treatment in everyday clinical practice.