Hasil untuk "Neurosciences. Biological psychiatry. Neuropsychiatry"

Hanlin Xiao, Rainer Breitling, Eriko Takano et al.

Recent advances in general-purpose foundation models have stimulated the development of large biological sequence models. While natural language shows symbolic granularity (characters, words, sentences), biological sequences exhibit hierarchical granularity whose levels (nucleotides, amino acids, protein domains, genes) further encode biologically functional information. In this paper, we investigate the integration of cross-granularity knowledge from models through a case study of BiGCARP, a Pfam domain-level model for biosynthetic gene clusters, and ESM, an amino acid-level protein language model. Using representation analysis tools and a set of probe tasks, we first explain why a straightforward cross-model embedding initialization fails to improve downstream performance in BiGCARP, and show that deeper-layer embeddings capture a more contextual and faithful representation of the model's learned knowledge. Furthermore, we demonstrate that representations at different granularities encode complementary biological knowledge, and that combining them yields measurable performance gains in intermediate-level prediction tasks. Our findings highlight cross-granularity integration as a promising strategy for improving both the performance and interpretability of biological foundation models.

Anna Arkhipova, Pavel Hok, Pavel Hok et al.

Creativity has been consensually defined as an ability to produce novel and original ideas/works, a definition shared both by the general public and among scholars. Since creativity is one of the most important and unique cognitive constructs seen in human beings, ways to enhance creativity have fascinated researchers across a broad range of human knowledge domains - from the arts and the humanities to science and technology. The functional process of creativity has been actively discussed not only in psychology, but also in neuroscience, where research is uncovering its neural correlates. A great amount of neuroimaging research has focused on describing anatomical and functional adaptations in the brain following various types of cognitive learning and training, e.g., classes of visual art or music composition, courses of drawing, calligraphy or playing musical instruments. A consistent underlying mechanism of domain-specific creativity has not yet been revealed due to difficulties in defining creativity or due to lack of generalizability across different modalities. On the other hand, recent studies suggest that there is a relationship between domain-general creativity and functional connectivity in particular brain networks. In this review, we discuss whether there is evidence for brain plasticity induced by training in creativity and associated behavioral changes, as well as whether the observed brain changes are consistent with the studies of neurobiological underpinnings of creativity and the changes induced by cognitive training.

Goutham Nalagatla, Shreyas Grandhe

Continual learning remains a fundamental challenge in artificial intelligence, with catastrophic forgetting posing a significant barrier to deploying neural networks in dynamic environments. Inspired by biological memory consolidation mechanisms, we propose a novel framework for generative replay that leverages predictive coding principles to mitigate forgetting. We present a comprehensive comparison between predictive coding-based and backpropagation-based generative replay strategies, evaluating their effectiveness on task retention and transfer efficiency across multiple benchmark datasets. Our experimental results demonstrate that predictive coding-based replay achieves superior retention performance (average 15.3% improvement) while maintaining competitive transfer efficiency, suggesting that biologically-inspired mechanisms can offer principled solutions to continual learning challenges. The proposed framework provides insights into the relationship between biological memory processes and artificial learning systems, opening new avenues for neuroscience-inspired AI research.

Conrad Möckel, Jiarui Li, Giulia Zanini et al.

Mass density is a vital property for improved biophysical understanding of and within biological samples. It is increasingly attracting active investigation, but still lacks reliable, non-contact techniques to accurately characterize it in biological systems. Contrary to popular belief, refractive index information alone is insufficient to determine a sample's mass density, as we demonstrate here theoretically and experimentally. Instead, we measured the nonlinear gain of stimulated Brillouin scattering to provide additional information for mass density estimation. This all-optical method reduces the estimation error tenfold, offering a more accurate and universal technique for mass density measurements.

Anastasia-Maria Leventi-Peetz, Jörg-Volker Peetz, Kai Weber et al.

In this work, a three-dimensional multicomponent reaction-diffusion model has been developed, combining excitable-system dynamics with diffusion processes and sharing conceptual features with the FitzHugh-Nagumo model. Designed to capture the spatiotemporal behavior of biological systems, particularly electrophysiological processes, the model was solved numerically to generate time-series data. These data were subsequently used to train and evaluate an Echo State Network (ESN), which successfully reproduced the system's dynamic behavior. The results demonstrate that simulating biological dynamics using data-driven, multifunctional ESN models is both feasible and effective.

Kevin Angers, Kourosh Darvish, Naruki Yoshikawa et al.

Automating biological experimentation remains challenging due to the need for millimeter-scale precision, long and multi-step experiments, and the dynamic nature of living systems. Current liquid handlers only partially automate workflows, requiring human intervention for plate loading, tip replacement, and calibration. Industrial solutions offer more automation but are costly and lack the flexibility needed in research settings. Meanwhile, research in autonomous robotics has yet to bridge the gap for long-duration, failure-sensitive biological experiments. We introduce RoboCulture, a cost-effective and flexible platform that uses a general-purpose robotic manipulator to automate key biological tasks. RoboCulture performs liquid handling, interacts with lab equipment, and leverages computer vision for real-time decisions using optical density-based growth monitoring. We demonstrate a fully autonomous 15-hour yeast culture experiment where RoboCulture uses vision and force feedback and a modular behavior tree framework to robustly execute, monitor, and manage experiments. Video demonstrations of RoboCulture can be found at https://ac-rad.github.io/roboculture.

Zhaoying Li, Shanyu Liu, Yuling Shen et al.

BackgroundAbnormalities in brain activity patterns during episodic memory tasks have been inconsistently reported in amnestic mild cognitive impairment (aMCI) patients using functional magnetic resonance imaging (fMRI). This study applied traditional Chinese medicine (TCM) syndrome differentiation to categorize aMCI patients into distinct subgroups, aiming to clarify the neural mechanisms underlying their cognitive profiles.MethodsParticipants included aMCI patients categorized into the turbid phlegm clouding the orifices (PCO) or spleen-kidney deficiency (SKD) syndrome subgroups, alongside cognitively normal controls (NC) matched for age and gender. Neuropsychological assessments were performed, and fMRI scans were acquired during an episodic memory task involving the recognition of new and old vocabulary. Brain activity across different stages of episodic memory was analyzed using SPM12 and DPABI 7.0 software.ResultsA total of 57 aMCI patients (34 with SKD and 23 with PCO) and 54 healthy controls were involved in the final task-based fMRI analysis. Compared with the NC group, the PCO group exhibited increased brain activation during both encoding and retrieval phases, primarily involving the prefrontal cortex and occipital lobe. Compared with the SKD group, the PCO group demonstrated the elevated activation in the right central sulcus and right insula during the encoding phase. Correlation analysis indicated a specific association between PCO symptom scores and insula activation. No statistically significant differences were found between the SKD and NC groups.ConclusionDistinct patterns of fMRI brain activity found in aMCI patients with PCO and SKD syndromes during episodic memory tasks suggest differing neural mechanisms that may contribute to the clinical heterogeneity of aMCI.

Chenyang Zang, MD, Zheng Xiao, MD, Luo Zhou, MD

Andrew Zillgitt, David E Burdette, Atheel Yako et al.

Clobazam (CLB) and cenobamate (CNB) are commonly used antiseizure medications (ASMs) in the treatment of patients with drug-resistant epilepsy (DRE). However, concomitant use of these two ASMs may lead to significant treatment-related adverse events (TRAE). Furthermore, these TRAE may be exacerbated in individuals with genetic polymorphisms involving the P450 system. In patients with DRE, epilepsy surgery, including neuromodulation, may lead to improved seizure control and a reduction in systemic TRAE from ASMs. This case report describes a patient with drug-resistant idiopathic generalized epilepsy (IGE) who experienced persistent excessive somnolence correlated with elevated N-desmethylclobazam (N-CLB) levels. Pharmacogenetic testing revealed poor metabolism of CYP2C19, and N-CLB levels remained elevated and detectable for nearly one year after the discontinuation of treatment with CLB and CNB. Responsive neurostimulator (RNS) implantation within the bilateral centromedian nuclei (CMN) of the thalamus resulted in seizure freedom until N-CLB levels fell, after which there was an 83–93 % reduction in the frequency of generalized tonic-clonic seizures (GTC).

Andrea Francesco Carluccio, Georg Northoff

Abstract Auditory verbal hallucinations [AVH] are one of the most common psychopathological symptoms in psychosis and schizophrenia [SZ]. While various studies demonstrate the neuronal features of AVH in specific regions and networks including changes in structural and functional connectivity, the relation of their neuronal topography to the organization or structure of the subjects’ experience, i.e. the phenomenology of their ‘mental topography’, remains yet unclear. Addressing this gap in our knowledge, we review recent findings to formulate two neurophenomenological hypotheses of AVH (which extend our earlier Resting state hypothesis). First, we hypothesize that structural and functional dysconnectivity in AVH with desynchronization and temporal fragmentation between sensory auditory, interoceptive somatic and cognitive linguistic regions [e.g., auditory cortex, insula and Broca’s area] relate to the experience of analogous temporal fragmentation on the mental level, that is, among the contents in perception and thought - this is manifest in ‘hyperreflexivity’, the attribution of abnormal salience and attention to single isolated objects or elements in perception. Secondly, we propose that the topographic distinction and gradient of unimodal and transmodal regions are reduced in individuals with AVH. We hypothesize that such ‘inner-outer neuronal topographic dedifferentiation and compression’ is manifest in the experience of overlaps and confusions between the subject’s outer interpersonal social and inner intrapersonal spaces – analogous to the neuronal level, this reflects an ‘inner-outer mental topographic dedifferentiation and compression’. Together, we propose two testable neurophenomenological hypotheses of AVH showing shared structural-topographic changes in both brain and experience as their “common currency”. This directly connects changes in the brain’s neuronal topographic organization with the structure of experience, that is, the mental topographic organization of the subjects’ experience of AVH in SZ.

Jijian Si, Yixin Zhang, Manyuan Li et al.

ObjectiveThis study aimed to examine the psychological mechanisms of depression in both bariatric surgery candidates and post-bariatric surgery patients and to explore the roles of resilience and anxiety in these relationships.MethodsA total of 431 candidates for bariatric surgery were recruited from a hospital. One month after the bariatric surgery, 228 patients continued to participate in the study. All participants completed the Insomnia Severity Index (ISI), Connor and Davidson Resilience Scale (CD-RISC), Generalized Anxiety Disorder 7-item scale (GAD-7), and Patient Health Questionnaire Depression Scale (PHQ-9). A mediation model analysis was used to investigate the mediating role of resilience, the mediating role of anxiety, and the chain mediating role of resilience and anxiety in the relationship between insomnia and depression.ResultsInsomnia positively correlated with depression through the mediating role of resilience, the mediating role of anxiety, and the serial mediating effect of resilience and anxiety among bariatric surgery candidates. However, only a direct effect of insomnia on depression and the mediating role of anxiety were found in post-bariatric surgery patients.ConclusionThe findings demonstrated that insomnia leads to an increase in depression among bariatric surgery patients, with resilience and anxiety playing significant mediating roles. This also highlights the need for targeted resilience-enhancing interventions in obese patients who are about to undergo bariatric surgery.

Will Dorrell, Kyle Hsu, Luke Hollingsworth et al.

Why do biological and artificial neurons sometimes modularise, each encoding a single meaningful variable, and sometimes entangle their representation of many variables? In this work, we develop a theory of when biologically inspired networks -- those that are nonnegative and energy efficient -- modularise their representation of source variables (sources). We derive necessary and sufficient conditions on a sample of sources that determine whether the neurons in an optimal biologically-inspired linear autoencoder modularise. Our theory applies to any dataset, extending far beyond the case of statistical independence studied in previous work. Rather we show that sources modularise if their support is ``sufficiently spread''. From this theory, we extract and validate predictions in a variety of empirical studies on how data distribution affects modularisation in nonlinear feedforward and recurrent neural networks trained on supervised and unsupervised tasks. Furthermore, we apply these ideas to neuroscience data, showing that range independence can be used to understand the mixing or modularising of spatial and reward information in entorhinal recordings in seemingly conflicting experiments. Further, we use these results to suggest alternate origins of mixed-selectivity, beyond the predominant theory of flexible nonlinear classification. In sum, our theory prescribes precise conditions on when neural activities modularise, providing tools for inducing and elucidating modular representations in brains and machines.

Peter J. Lawrence, Simona Skripkauskaite, Adrienne Shum et al.

Abstract Background The COVID‐19 pandemic caused significant disruption to the lives of children and their families. Pre‐school children may have been particularly vulnerable to the effects of the pandemic, with the closure of childcare facilities, playgrounds, playcentres and parent and toddler groups limiting their opportunities for social interaction at a crucial stage of development. Additionally, for parents working from home, caring for pre‐school aged children who require high levels of support and care, was likely challenging. We conducted an intensive longitudinal, but not nationally representative, study to examine trajectories of pre‐schoolers’ mental symptoms in the United Kingdom during the first year of the COVID‐19 pandemic. Methods UK‐based parents and carers (n = 1520) of pre‐school‐aged children (2–4 years) completed monthly online surveys about their pre‐schoolers’ mental health between April 2020 and March 2021. The survey examined changes in children's emotional symptoms, conduct problems and hyperactivity/inattention. Results In our final mixed‐effects models, our predictors (fixed effects) accounted for 5% of the variance in each of conduct problems, emotional symptoms and hyperactivity/inattention symptoms scores, and the combined random and fixed effects accounted for between 64% and 73% of the variance. Pre‐schoolers’ emotional problems and hyperactivity/inattention symptoms declined from April through summer 2020 and then increased again during the autumn and winter 2020/2021 as lockdowns were re‐introduced. Pre‐schoolers who attended childcare showed greater decline in symptom severity than those who did not. Older children, compared to younger, showed greater lability of emotion symptom severity. Attending childcare predicted lower symptom severity across all three domains of conduct problems, emotional symptoms, and hyperactivity/inattention, while the opposite pattern was observed for children whose parent had a mental health problem. Conclusions Our findings reinforce the importance of examining pre‐schoolers’ mental health in the context of micro and macro‐level factors. Interventions focussing on family factors such as parent mental health, as well as continued provision of childcare, may have most potential to mitigate the impact of COVID‐19 on young children's mental health.

Sofia Leonardo, Felipe Fregni

BackgroundThe development of mild cognitive impairment (MCI) and Alzheimer’s disease (AD) may be associated with an inflammatory process. Inflammatory cytokines may be a surrogate for systemic inflammation leading to worsening neurological function. We aim to investigate the association between cognitive impairment and inflammation by pooling and analyzing the data from previously published studies.MethodsWe performed a systematic literature search on MEDLINE, PubMed, Embase, Web of Science, and Scopus for prospective longitudinal and cross-sectional studies evaluating the relationship between inflammation and cognitive functions.ResultsA total of 79 articles were included in our systematic review and meta-analysis. Pooled estimates from cross-sectional studies have demonstrated an increased level of C-reactive protein (CRP) [Hedges’s g 0.35, 95% CI (0.16, 0.55), p < 0.05], IL-1β [0.94, 95% CI (−0.04, 1.92), p < 0.05], interleukin-6 (IL-6) [0.46, 95% CI (0.05, 0.88), p < 0.005], TNF alpha [0.22, 95% CI (−0.24, 0.68), p < 0.05], sTNFR-1 [0.74, 95% CI (0.46, 1.02), p < 0.05] in AD compared to controls. Similarly, higher levels of IL-1β [0.17, 95% CI (0.05, 0.28), p < 0.05], IL-6 [0.13, 95% CI (0.08, 0.18), p < 0.005], TNF alpha [0.28, 95% CI (0.07, 0.49), p < 0.05], sTNFR-1 [0.21, 95% CI (0.05, 0.48), p < 0.05] was also observed in MCI vs. control samples. The data from longitudinal studies suggested that levels of IL-6 significantly increased the risk of cognitive decline [OR = 1.34, 95% CI (1.13, 1.56)]. However, intermediate levels of IL-6 had no significant effect on the final clinical endpoint [OR = 1.06, 95% CI (0.8, 1.32)].ConclusionThe data from cross-sectional studies suggest a higher level of inflammatory cytokines in AD and MCI as compared to controls. Moreover, data from longitudinal studies suggest that the risk of cognitive deterioration may increase by high IL-6 levels. According to our analysis, CRP, antichymotrypsin (ACT), Albumin, and tumor necrosis factor (TNF) alpha may not be good surrogates for neurological degeneration over time.

Jianbin Sun, Jianbin Sun, Jianbin Sun et al.

IntroductionSymptoms induced by arachnoid cysts in the fallopian canal are uncommon, and facial nerve paralysis without cerebrospinal fluid otorrhea is comparatively rarer.MethodsHerein, we present two cases of arachnoid cysts in the fallopian canal with acute severe facial nerve paralysis and review the relevant literature.ResultsThe symptoms and imaging findings of these two cases resembled those of facial nerve schwannomas. Cerebrospinal fluid otorrhea occurred upon removal of the arachnoid cyst, and the facial nerve was observed to be separated into multiple filaments or compressed and atrophied. Facial-hypoglossal nerve anastomosis and decompression were conducted after packing the dehiscence of cerebrospinal fluid otorrhea for the two cases.ConclusionArachnoid cysts of the fallopian canal rarely cause facial nerve paralysis. Enhanced magnetic resonance imaging is vital for differentiating schwannomas. Different treatment strategies should be adopted for patients with different degrees of facial nerve paralysis; however, concurrent repair of cerebrospinal fluid otorrhea and facial nerves during surgery can occasionally be challenging.

Klaus Thanke Aspli, Jan O. Aaseth, Trygve Holmøy et al.

Skogholt’s disease is a rare neurological disorder that is only observed in a small Norwegian kindred. It typically manifests in adulthood with uncharacteristic neurological symptoms from both the peripheral and central nervous systems. The etiology of the observed cerebral white matter lesions and peripheral myelin pathology is unclear. Increased cerebrospinal fluid (CSF) concentrations of protein have been confirmed, and recently, very high concentrations of CSF total and phosphorylated tau have been detected in Skogholt patients. The symptoms and observed biomarker changes in Skogholt’s disease are largely nonspecific, and further studies are necessary to elucidate the disease mechanisms. Here, we report the results of neurochemical analyses of plasma and CSF, as well as results from the morphometric segmentation of cerebral magnetic resonance imaging. We analyzed the biomarkers Aβ_1––42, Aβ_1–40, Aβ_x–38, Aβ_x–40, Aβ_x–42, total and phosphorylated tau, glial fibrillary acidic protein, neurofilament light chain, platelet-derived growth factor receptor beta, and beta-trace protein. All analyzed CSF biomarkers, except neurofilament light chain and Aβ_1/x–42, were increased several-fold. In blood, none of these biomarkers were significantly different between the Skogholt and control groups. MRI volumetric segmentation revealed decreases in the ventricular, white matter, and choroid plexus volumes in the Skogholt group, with an accompanying increase in white matter lesions. The cortical thickness and subcortical gray matter volumes were increased in the Skogholt group. Pathophysiological changes resulting from choroidal dysfunction and/or abnormal CSF turnover, which may cause the increases in CSF protein and brain biomarker levels, are discussed.

Carina França, Rafael Bernhart Carra, Juliete Melo Diniz et al.

ABSTRACT For more than 30 years, Deep Brain Stimulation (DBS) has been a therapeutic option for Parkinson’s disease (PD) treatment. However, this therapy is still underutilized mainly due to misinformation regarding risks and clinical outcomes. DBS can ameliorate several motor and non-motor symptoms, improving patients’ quality of life. Furthermore, most of the improvement after DBS is long-lasting and present even in advanced PD. Adequate patient selection, precise electric leads placement, and correct DBS programming are paramount for good surgical outcomes. Nonetheless, DBS still has many limitations: axial symptoms and signs, such as speech, balance and gait, do not improve to the same extent as appendicular symptoms and can even be worsened as a direct or indirect consequence of surgery and stimulation. In addition, there are still unanswered questions regarding patient’s selection, surgical planning and programming techniques, such as the role of surgicogenomics, more precise imaging-based lead placement, new brain targets, advanced programming strategies and hardware features. The net effect of these innovations should not only be to refine the beneficial effect we currently observe on selected symptoms and signs but also to improve treatment resistant facets of PD, such as axial and non-motor features. In this review, we discuss the current state of the art regarding DBS selection, implant, and programming, and explore new advances in the DBS field.

Cornelia Geßner, Alena Krüger, Lars P. Folkow et al.

The mammalian brain is characterized by high energy expenditure and small energy reserves, making it dependent on continuous vascular oxygen and nutritional supply. The brain is therefore extremely vulnerable to hypoxia. While neurons of most terrestrial mammals suffer from irreversible damage after only short periods of hypoxia, neurons of the deep-diving hooded seal (Cystophora cristata) show a remarkable hypoxia-tolerance. To identify the molecular mechanisms underlying the intrinsic hypoxia-tolerance, we excised neurons from the visual cortices of hooded seals and mice (Mus musculus) by laser capture microdissection. A comparison of the neuronal transcriptomes suggests that, compared to mice, hooded seal neurons are endowed with an enhanced aerobic metabolic capacity, a reduced synaptic transmission and an elevated antioxidant defense. Publicly available whole-tissue brain transcriptomes of the bowhead whale (Balaena mysticetus), long-finned pilot whale (Globicephala melas), minke whale (Balaenoptera acutorostrata) and killer whale (Orcinus orca), supplemented with 2 newly sequenced long-finned pilot whales, suggest that, compared to cattle (Bos taurus), the cetacean brain also displays elevated aerobic capacity and reduced synaptic transmission. We conclude that the brain energy balance of diving mammals is preserved during diving, due to reduced synaptic transmission that limits energy expenditure, while the elevated aerobic capacity allows efficient use of oxygen to restore energy balance during surfacing between dives.

Yair Ben Sahel, John P. Bryan, Brian Cleary et al.

Deep algorithm unrolling has emerged as a powerful model-based approach to develop deep architectures that combine the interpretability of iterative algorithms with the performance gains of supervised deep learning, especially in cases of sparse optimization. This framework is well-suited to applications in biological imaging, where physics-based models exist to describe the measurement process and the information to be recovered is often highly structured. Here, we review the method of deep unrolling, and show how it improves source localization in several biological imaging settings.

F. Meloni, G. Nakamura, B. Grammaticos et al.

The far-reaching consequences of ecological interactions in the dynamics of biological communities remain an intriguing subject. For decades, competition has been a cornerstone in ecological processes, but mounting evidence shows that cooperation does also contribute to the structure of biological communities. Here, we propose a simple deterministic model for the study of the effects of facilitation and competition in the dynamics of such systems. The simultaneous inclusion of both effects produces rich dynamics and captures the context-dependence observed in the formation of ecological communities. The approach reproduces relevant aspects of primary and secondary plant succession, the effect invasive species, and the survival of rare species. The model also takes into account the role of the ecological priority effect and stress the crucial role of facilitation in conservation efforts and species coexistence.