Hasil untuk "Neurosciences. Biological psychiatry. Neuropsychiatry"

Simeng Zhang, Xinying Liu, Jun Lou et al.

The rapid development of high-throughput sequencing technologies has led to an explosive increase in biological sequence data, making sequence clustering a fundamental task in large-scale bioinformatics analyses. Unlike traditional clustering problems, biological sequence clustering faces unique challenges due to the lack of direct similarity measures, strict biological constraints, and demanding requirements for both scalability and accuracy. Over the past decades, a wide variety of methods have been developed, differing in how they model sequence similarity, construct clusters, and prioritize optimization objectives. In this review, we provide a comprehensive methodological overview of biological sequence clustering algorithms. We begin by summarizing the main strategies for modeling sequence similarity, which can be divided into three stages: sequence encoding, feature generation, and similarity measurement. Next, we discuss the major clustering paradigms, including greedy incremental, hierarchical, graph-based, model-based, partitional, and deep learning approaches, highlighting their methodological characteristics and practical trade-offs. We then discuss clustering objectives from three key perspectives: scalability and resource efficiency, biological interpretability, and robustness and clustering quality. Organizing existing methods along these dimensions allows us to explore the trade-offs in biological sequence clustering and clarify the contexts in which different approaches are most appropriate. Finally, we identify current limitations and challenges, providing guidance for researchers and directions for future method development.

James C. R. Whittington, William Dorrell

How much of the brain's learned algorithms depend on the fact it is a brain? We argue: a lot, but surprisingly few details matter. We point to simple biological details -- e.g. nonnegative firing and energetic/space budgets in connectionist architectures -- which, when mixed with the requirements of solving a task, produce models that predict brain responses down to single-neuron tuning. We understand this as details constraining the set of plausible algorithms, and their implementations, such that only `brain-like' algorithms are learned. In particular, each biological detail breaks a symmetry in connectionist models (scale, rotation, permutation) leading to interpretable single-neuron responses that are meaningfully characteristic of particular algorithms. This view helps us not only understand the brain's choice of algorithm but also infer algorithm from measured neural responses. Further, this perspective aligns computational neuroscience with mechanistic interpretability in AI, suggesting a more unified approach to studying the mechanisms of intelligence, both natural and artificial.

Sirui Ning, Yannick A. D. Omar, Karthik Shekhar et al.

Understanding how electric fields destabilize biological membranes is important for electroporation-based technologies and bioelectronic interfaces. However, theoretical descriptions of this phenomenon remain fragmented. Existing theories treat either electrostatics in membranes of finite thickness or electrohydrodynamic flows at idealized zero-thickness interfaces, leaving unresolved a unified description that simultaneously incorporates finite membrane thickness, surface charge, and bulk electrohydrodynamics. Here, we apply a recently-developed, dimension-reduction framework that captures the coupled electrohydrodynamic and mechanical effects governing height fluctuations of a charged lipid bilayer of thickness $δ$ in an electrolyte characterized by Debye screening length $λ$. We derive voltage- and charge-dependent renormalizations of the effective surface tension and bending rigidity, along with a dispersion relation governing undulatory instabilities. A wide range of prior theoretical results arise as limiting cases of our more general theory when finite-thickness effects are neglected or screening is asymptotically strong. The key new contribution arises from traction moments generated across the finite membrane thickness, which are absent in zero-thickness descriptions. Under physiological screening ($δ/λ\sim 4$), these contributions account for more than $>70\%$ of the total electrostatic correction to both surface tension and bending rigidity. The theory further reveals that surface charges can stabilize the membrane at physiological ionic strengths, increasing the effective tension and shifting electroporation thresholds in a manner that depends on charge asymmetry between the leaflets.

Simen Jacobs, Julian B. Voits, Nikita Frolov et al.

Building on the phenomenological and microscopic models reviewed in Part I, this second part focuses on network-level mechanisms that generate emergent temperature response curves. We review deterministic models in which temperature modulates the kinetics of coupled biochemical reactions, as well as stochastic frameworks, such as Markov chains, that capture more complex multi-step processes. These approaches show how Arrhenius-like temperature dependence at the level of individual reactions is transformed into non-Arrhenius scaling, thermal limits, and temperature compensation at the system level. Together, network-level models provide a mechanistic bridge between empirical temperature response curves and the molecular organization of biological systems, giving us predictive insights into robustness, perturbations, and evolutionary constraints.

Peter Koenig, Mario Negrello

Neuroscience has long informed the development of artificial neural networks, but the success of modern architectures invites, in turn, the converse: can modern networks teach us lessons about brain function? Here, we examine the structure of the cortical column and propose that the transformer provides a natural computational analogy for multiple elements of cortical microcircuit organization. Rather than claiming a literal implementation of transformer equations in cortex, we develop a hypothetical mapping between transformer operations and laminar cortical features, using the analogy as an orienting framework for analysis and discussion. This mapping allows us to examine in greater depth how contextual selection, content routing, recurrent integration, and interlaminar transformations may be distributed across cortical circuitry. In doing so, we generate a broad set of predictions and experimentally testable hypotheses concerning laminar specialization, contextual modulation, dendritic integration, oscillatory coordination, and the effective connectivity of cortical columns. This proposal is intended as a structured hypothesis rather than a definitive account of cortical computation. Placing transformer operations and cortical architectonics into a common descriptive framework sharpens questions, reveals new functional correspondences, and opens a productive route for reciprocal exchange between systems neuroscience and modern AI. More broadly, this perspective suggests that comparing brains and architectures at the level of computational organization can yield genuine insight into both.

Yasin Taşkın, Fatih Ersay Deniz, Veysel Kıyak et al.

Abstract Background This study aimed to evaluate the histomorphological cellular and fibrotic responses in rat brain tissue following direct placement of platinum coils, simulating potential coil protrusion or extravasation scenarios encountered during endovascular treatment of ruptured intracranial aneurysms. Methods A burr hole was made in the biparietal bone region of 40 Winstar albino rats to pass through the dura and pia mater, and a platinum coil was placed in the interhemispheric area. The rats were sacrificed on days 3 and 10 to evaluate the changes in the acute and chronic periods, respectively. Subsequently, brain tissues were removed and histomorphological changes were examined. Results The lowest amount of reparative tissue in the treated area was formed in the coil + 3-day group, whereas the highest amount of reparative tissue was formed in the coil-free 10-day group. Further, the amount of reparative tissue in the coil-free 3-day group and the coil + 10-day group was high compared to the coil + 3-day group, whereas low compared to the coil-free 10-day group. These two groups (coil-free 3-day and coil + 10-day) were statistically similar to each other and different from the others. Conclusıons Platinum coil is expected to reduce the development of tissue reaction, which may be a disadvantage for the development of complete occlusion; however, it is important for reducing the possibility of thromboembolism and showing that the protruding coil has no irritating effect on brain tissue.

Alexander Ororbia, Ankur Mali, Adam Kohan et al.

One major criticism of deep learning centers around the biological implausibility of the credit assignment schema used for learning -- backpropagation of errors. This implausibility translates into practical limitations, spanning scientific fields, including incompatibility with hardware and non-differentiable implementations, thus leading to expensive energy requirements. In contrast, biologically plausible credit assignment is compatible with practically any learning condition and is energy-efficient. As a result, it accommodates hardware and scientific modeling, e.g. learning with physical systems and non-differentiable behavior. Furthermore, it can lead to the development of real-time, adaptive neuromorphic processing systems. In addressing this problem, an interdisciplinary branch of artificial intelligence research that lies at the intersection of neuroscience, cognitive science, and machine learning has emerged. In this paper, we survey several vital algorithms that model bio-plausible rules of credit assignment in artificial neural networks, discussing the solutions they provide for different scientific fields as well as their advantages on CPUs, GPUs, and novel implementations of neuromorphic hardware. We conclude by discussing the future challenges that will need to be addressed in order to make such algorithms more useful in practical applications.

Suryanarayana Maddu, Victor Chardès, Michael. J. Shelley

Inferring dynamical models from data continues to be a significant challenge in computational biology, especially given the stochastic nature of many biological processes. We explore a common scenario in omics, where statistically independent cross-sectional samples are available at a few time points, and the goal is to infer the underlying diffusion process that generated the data. Existing inference approaches often simplify or ignore noise intrinsic to the system, compromising accuracy for the sake of optimization ease. We circumvent this compromise by inferring the phase-space probability flow that shares the same time-dependent marginal distributions as the underlying stochastic process. Our approach, probability flow inference (PFI), disentangles force from intrinsic stochasticity while retaining the algorithmic ease of ODE inference. Analytically, we prove that for Ornstein-Uhlenbeck processes the regularized PFI formalism yields a unique solution in the limit of well-sampled distributions. In practical applications, we show that PFI enables accurate parameter and force estimation in high-dimensional stochastic reaction networks, and that it allows inference of cell differentiation dynamics with molecular noise, outperforming state-of-the-art approaches.

Natàlia Fort, Anaïs Orobitg

Behdad Parhizi, Trevor S. Barss, Alphonso Martin Dineros et al.

Abstract Humans use their arms in complex ways that often demand two-handed coordination. Neurological conditions limit this impressive feature of the human motor system. Understanding how neuromodulatory techniques may alter neural mechanisms of bimanual coordination is a vital step towards designing efficient rehabilitation interventions. By non-invasively activating the spinal cord, transcutaneous spinal cord stimulation (tSCS) promotes recovery of motor function after spinal cord injury. A multitude of research studies have attempted to capture the underlying neural mechanisms of these effects using a variety of electrophysiological tools, but the influence of tSCS on cortical rhythms recorded via electroencephalography remains poorly understood, especially during bimanual actions. We recruited 12 neurologically intact participants to investigate the effect of cervical tSCS on sensorimotor cortical oscillations. We examined changes in the movement kinematics during the application of tSCS as well as the cortical activation level and interhemispheric connectivity during the execution of unimanual and bimanual arm reaching movements that represent activities of daily life. Behavioral assessment of the movements showed improvement of movement time and error during a bimanual common-goal movement when tSCS was delivered, but no difference was found in the performance of unimanual and bimanual dual-goal movements with the application of tSCS. In the alpha band, spectral power was modulated with tSCS in the direction of synchronization in the primary motor cortex during unimanual and bimanual dual-goal movements and in the somatosensory cortex during unimanual movements. In the beta band, tSCS significantly increased spectral power in the primary motor and somatosensory cortices during the performance of bimanual common-goal and unimanual movements. A significant increase in interhemispheric connectivity in the primary motor cortex in the alpha band was only observed during unimanual tasks in the presence of tSCS. Our observations provide, for the first time, information regarding the supra-spinal effects of tSCS as a neuromodulatory technique applied to the spinal cord during the execution of bi- and unimanual arm movements. They also corroborate the suppressive effect of tSCS at the cortical level reported in previous studies. These findings may guide the design of improved rehabilitation interventions using tSCS for the recovery of upper-limb function in the future.

Lukas J. Meier

Chabard es, S., M. Polosan, P. Krack, J. Bastin, A. Krainik, O. David, T. Bougerol, and A. L. Benabid. 2013. Deep brain stimulation for obsessive-compulsive disorder: Subthalamic nucleus target. World Neurosurgery 80 (3–4): S31.e1–8–S31.e8. doi:10.1016/j.wneu.2012.03.010. Gilbert, F., J. Noel, M. Via~ na, and C. Ineichen. 2021. Deflating the “DBS causes personality changes” bubble. Neuroethics 14 (S1):1–17. doi:10.1007/s12152-018-9373-8. Huys, Q. J. M., T. V. Maia, and M. J. Frank. 2016. Computational psychiatry as a bridge from neuroscience to clinical applications. Nature Neuroscience 19 (3):404– 13. doi:10.1038/nn.4238. Kubu, C. S., S. E. Cooper, A. Machado, T. Frazier, J. Vitek, and P. J. Ford. 2017. Insights gleaned by measuring patients’ stated goals for DBS: More than tremor. Neurology 88 (2):124–30. doi:10.1212/WNL.0000000000003485. Le Heron, C., C. B. Holroyd, J. Salamone, and M. Husain. 2019. Brain mechanisms underlying apathy. Journal of Neurology, Neurosurgery, and Psychiatry 90 (3):302–12. doi:10.1136/jnnp-2018-318265. Rossi, P. J., A. Gunduz, and M. S. Okun. 2015. The subthalamic nucleus, limbic function, and impulse control. Neuropsychology Review 25 (4):398–410. doi:10.1007/ s11065-015-9306-9. Seritan, A. L., L. L. Spiegel, J. L. Weinstein, C. A. Racine, E. G. Brown, M. Volz, C. de Hemptinne, P. A. Starr, and J. L. Ostrem. 2021. Elevated mood states in patients with Parkinson’s disease treated with deep brain stimulation: Diagnosis and management strategies. The Journal of Neuropsychiatry and Clinical Neurosciences 33 (4):314–20. doi:10.1176/appi.neuropsych.20080205. Zuk, P., C. E. Sanchez, K. Kostick-Quenet, K. A. Mu~ noz, L. Kalwani, R. Lavingia, L. Torgerson, D. Sierra-Mercado, J. O. Robinson, S. Pereira, et al. 2023. Researcher views on changes in personality, mood, and behavior in nextgeneration deep brain stimulation. AJOB Neuroscience 14 (3):287–299. doi:10.1080/21507740.2022.2048724.

Aran Nayebi

Humans and animals exhibit a range of interesting behaviors in dynamic environments, and it is unclear how our brains actively reformat this dense sensory information to enable these behaviors. Experimental neuroscience is undergoing a revolution in its ability to record and manipulate hundreds to thousands of neurons while an animal is performing a complex behavior. As these paradigms enable unprecedented access to the brain, a natural question that arises is how to distill these data into interpretable insights about how neural circuits give rise to intelligent behaviors. The classical approach in systems neuroscience has been to ascribe well-defined operations to individual neurons and provide a description of how these operations combine to produce a circuit-level theory of neural computations. While this approach has had some success for small-scale recordings with simple stimuli, designed to probe a particular circuit computation, often times these ultimately lead to disparate descriptions of the same system across stimuli. Perhaps more strikingly, many response profiles of neurons are difficult to succinctly describe in words, suggesting that new approaches are needed in light of these experimental observations. In this thesis, we offer a different definition of interpretability that we show has promise in yielding unified structural and functional models of neural circuits, and describes the evolutionary constraints that give rise to the response properties of the neural population, including those that have previously been difficult to describe individually. We demonstrate the utility of this framework across multiple brain areas and species to study the roles of recurrent processing in the primate ventral visual pathway; mouse visual processing; heterogeneity in rodent medial entorhinal cortex; and facilitating biological learning.

Sarah R. Ocañas, Kevin D. Pham, Jillian E. J. Cox et al.

Abstract Background Microglia, the brain’s principal immune cells, have been implicated in the pathogenesis of Alzheimer’s disease (AD), a condition shown to affect more females than males. Although sex differences in microglial function and transcriptomic programming have been described across development and in disease models of AD, no studies have comprehensively identified the sex divergences that emerge in the aging mouse hippocampus. Further, existing models of AD generally develop pathology (amyloid plaques and tau tangles) early in life and fail to recapitulate the aged brain environment associated with late-onset AD. Here, we examined and compared transcriptomic and translatomic sex effects in young and old murine hippocampal microglia. Methods Hippocampal tissue from C57BL6/N and microglial NuTRAP mice of both sexes were collected at young (5–6 month-old [mo]) and old (22–25 mo) ages. Cell sorting and affinity purification techniques were used to isolate the microglial transcriptome and translatome for RNA-sequencing and differential expression analyses. Flow cytometry, qPCR, and imaging approaches were used to confirm the transcriptomic and translatomic findings. Results There were marginal sex differences identified in the young hippocampal microglia, with most differentially expressed genes (DEGs) restricted to the sex chromosomes. Both sex chromosomally and autosomally encoded sex differences emerged with aging. These sex DEGs identified at old age were primarily female-biased and enriched in senescent and disease-associated microglial signatures. Normalized gene expression values can be accessed through a searchable web interface ( https://neuroepigenomics.omrf.org/ ). Pathway analyses identified upstream regulators induced to a greater extent in females than in males, including inflammatory mediators IFNG, TNF, and IL1B, as well as AD-risk genes TREM2 and APP. Conclusions These data suggest that female microglia adopt disease-associated and senescent phenotypes in the aging mouse hippocampus, even in the absence of disease pathology, to a greater extent than males. This sexually divergent microglial phenotype may explain the difference in susceptibility and disease progression in the case of AD pathology. Future studies will need to explore sex differences in microglial heterogeneity in response to AD pathology and determine how sex-specific regulators (i.e., sex chromosomal or hormonal) elicit these sex effects.

Olga Winkler, Lisa Burback, Andrew J. Greenshaw et al.

Caring for patients with personality disorders can be challenging due to risks associated with suicidal ideation, homicidal threats, splitting, and acting out with problematic behavior in psychiatric inpatient units. Limited resources on inpatient units further add to the stress and burden on staff. This case summarizes how trauma-informed care was implemented in an inpatient setting to produce marked improvement in a patient’s treatment outcomes as well as better staff engagement and satisfaction. This culture change in the approach to care was not an easy process, as effortful planning and resources were required for key elements such as ongoing coaching, education, and regular staff debriefings. This case report signals the need for service providers to enable health systems to examine rules and exceptions from a cultural perspective of considering equity, diversity, and inclusion (EDI)—to allow openness to rational exceptions, even if they are unconventional.

Martina Sebök, Lara Höbner, Jorn Fierstra et al.

Andy Wai Kan Yeung, Maya G. Georgieva, A. Atanasov et al.

Background: Monoamine oxidases (MAOs) were discovered nearly a century ago. This article aims to analyze the research literature landscape associated with MAOs as privileged class of neuronal enzymes (neuroenzymes) with key functions in the processes of neurodegeneration, serving as important biological targets in neuroscience. With the accumulating publications on this topic, we aimed to evaluate the publication and citation performance of the contributors, reveal the popular research themes, and identify its historical roots. Methods: The electronic database of Web of Science (WoS) Core Collection was searched to identify publications related to MAOs, which were analyzed according to their publication year, authorship, institutions, countries/regions, journal title, WoS category, total citation count, and publication type. VOSviewer was utilized to visualize the citation patterns of the words appearing in the titles and abstracts, and author keywords. CRExplorer was utilized to identify seminal references cited by the MAO publications. Results: The literature analysis was based on 19,854 publications. Most of them were original articles (n = 15,148, 76.3%) and reviews (n = 2,039, 10.3%). The top five WoS categories of the analyzed MAO publications were Pharmacology/Pharmacy (n = 4,664, 23.5%), Neurosciences (n = 4,416, 22.2%), Psychiatry (n = 2,906, 14.6%), Biochemistry/Molecular Biology (n = 2,691, 13.6%), and Clinical Neurology (n = 1,754, 8.8%). The top 10 institutions are scattered in the United States, UK, France, Sweden, Canada, Israel, and Russia, while the top 10 countries/regions with the most intensive research on the field of MAOs are the United States, followed by European and Asian countries. More highly cited publications generally involved neurotransmitters, such as dopamine (DA), serotonin, and norepinephrine (NE), as well as the MAO-A inhibitors moclobemide and clorgyline, and the irreversible MAO-B inhibitors selegiline and rasagiline. Conclusion: Through decades of research, the literature has accumulated many publications investigating the therapeutic effects of MAO inhibitors (MAOIs) on various neurological conditions, such as Alzheimer’s disease (AD), Parkinson’s disease (PD), and depression. We envision that MAO literature will continue to grow steadily, with more new therapeutic candidates being tested for better management of neurological conditions, in particular, with the development of multi-target acting drugs against neurodegenerative diseases.

Rajendra Singh Jain, P V Sripadma, Shankar Tejwani

Background: Recanalization rates in cerebral venous thrombosis (CVT) and its effect on neurological outcome have been debated worldwide and are inadequately addressed in studies from India. Our objective was to study the clinical profile of CVT and determine recanalization rates with its predictors and its effect on outcome. Methods: A prospective single centre cohort study on 101 patients with radiologically confirmed acute CVT between October 2018 and June 2021 was conducted. Anticoagulation was given for 3-12 months or lifelong for thrombophilias. Recanalization status of vessels was assessed between 3-6 months and at 12 months after ictus. Outcome was defined as favorable (mRS 0-1) or unfavorable. Patients with atleast one CT/MR venogram on follow up were included. Results: Of the 101 enrolled patients, 83 completed study protocol. Mean age of patients was 34.2 ± 11.7 years. Clinical characteristics included headache (75.9%),seizure (66.2%), altered mentation(20.4%) with clustering of cases during summers. Transverse- sigmoid sinuses were predominantly involved (66.2 %) followed by superior sagittal sinus (SSS,65.0%). Commonest etiologies were thrombophilia (27.7%) and postpartum state (15.6%). Complete recanalization was achieved in 67.4%, partial in 26.5% and no recanalization in 6.02% at end of 12 months. Recanalization rates improved from 83.09% between 3-6 months to 93.9 % at 12 months. Median time to last follow-up was 12months and at last follow up 95.1% had favorable mRS with recurrence in two patients with raised factor VIII levels. Conclusion: Recanalization occurred in more than 90% of CVT patients. Isolated superior sagittal sinus thrombosis and age <50 years were predictors of complete recanalization. Most patients, except few achieved a favorable mRS.

Carolina Widinghoff, Jonas Berge, M. Wallinius et al.

1 Department of Clinical Sciences Lund, Psychiatry, Faculty of Medicine, Lund University, Lund, Sweden 2 Clinical Research Unit/Gambling Disorder Unit, Malmö Addiction Center, 205 02 Malmö, Region Skåne, Sweden 3 Faculty of Medicine, Department of Clinical Sciences, Lund, Child and Adolescent Psychiatry, Lund University, Lund, Sweden 4 Regional Forensic Psychiatric Clinic, Växjö, Sweden 5 Department of Psychiatry and Neurochemistry, Centre for Ethics, Law and Mental Health, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at University of Gothenburg, Gothenburg, Sweden 6 Gillberg Neuropsychiatry Centre, Institute of Neuroscience and Physiology, Sahlgrenska Academy at the University of Gothenburg, Gothenburg, Sweden 7 Division of Forensic Psychiatry, Faculty of Medicine, Department of Clinical Sciences, Lund, Child and Adolescent Psychiatry, Lund University, Lund, Region Skåne, Sweden Correction to: Journal of Gambling Studies (2019) 35:485–500 https:// doi. org/ 10. 1007/ s108990189785-8

A. Sanati

Dr Deeley is an honorary consultant neuropsychiatrist in the National Autism Unit at Bethlem Royal Hospital and in the Neuropsychiatry Brain Injury Clinic at the Maudsley Hospital, two hospitals within South London and Maudsley NHS Foundation Trust. He is also a senior lecturer in forensic and neurodevelopmental sciences at the Institute of Psychiatry, Psychology & Neuroscience (IOPPN), King’s College London. He chairs the Cultural and Social Neuroscience Research Group at the IOPPN and the Maudsley Philosophy Group.

D. Eratne, D. Velakoulis

1 Neuropsychiatry Unit, The Royal Melbourne Hospital, Parkville, VIC, Australia 2 Melbourne Neuropsychiatry Centre, The University of Melbourne & NorthWestern Mental Health, Melbourne, VIC, Australia 3 Department of Psychiatry, The University of Melbourne, Melbourne, VIC, Australia 4 National Dementia Diagnostics Laboratory, Florey Institute of Neuroscience and Mental Health, The University of Melbourne, Melbourne, VIC, Australia