Search Results (2,692)

Electrochemical sensors are user-friendly devices designed for the rapid and straightforward detection of target analytes. Serotonin (5-hydroxytryptamine, 5-HT) is a key neurotransmitter and neuromodulator that regulates diverse neuronal processes. Using a custom-designed screen-printed carbon electrode (SPCE) incorporating ordered mesoporous carbon–bimetal oxides of Cu and Ni (CuO–NiO–OMC), rapid and real-time detection of 5-HT was achieved. The CuO–NiO–OMC structure featured highly active CuO and NiO catalytic sites that effectively promoted the irreversible oxidation of 5-HT (vs. Ag/AgCl reference electrode). The CuO–NiO–OMC/SPCE sensor, connected to a portable potentiostat, exhibited exceptional electrocatalytic performance for the oxidation of 5-HT, with a detection limit of 42.5 nM. The sensitivity was 1.56 A M⁻¹ cm⁻², and the linear dynamic range was 0.0–80.0 µM. The CuO–NiO–OMC/SPCE sensor also demonstrated outstanding selectivity in the presence of competing neurochemicals, including norepinephrine, epinephrine, dopamine, and glutamate, as well as high concentrations of tested biomolecules and inorganic ions. Furthermore, the practicality of the sensor was demonstrated using human serum and urine samples, with recovery percentages ranging from 91.1% to 98.3%. Thus, the CuO–NiO–OMC/SPCE sensor offers an effective approach for 5-HT sensing, thereby permitting molecular-level understanding of brain function. Full article

Continuous representations in brain navigation system are manifested as spatially structured patterns of population activity, such as a single-peaked bump moving along a ring manifold in head-direction system and hexagonal lattice patterns underlying spatial representation in grid-cell systems. These phenomena are commonly modelled within the framework of continuous attractor networks (neural dynamical field), yet the mechanisms by which activation-function nonlinearities interact with connectivity structure to determine pattern selection and dynamics remain incompletely understood. This paper separately analyses the interactions between non-resonant and resonant modes using a multiscale unfolding approach. We show that, when the critical modes satisfy a resonance condition, the quadratic nonlinearity of the activation function induces a three-mode coupling that fundamentally alters the structure of the amplitude equations and becomes the dominant mechanism governing spatial pattern selection. Building on this analysis, we introduce a weak asymmetric component in the connectivity and analytically derive the resulting pattern drift velocity, which is subsequently confirmed by numerical simulations. Finally, we apply these dynamical mechanisms to input-driven scenarios, illustrating that similar dynamical mechanisms can account for activity-bump tracking in head-direction models and lattice translations in grid-cell models. Overall, this work provides an analytically tractable framework for studying pattern dynamics in neural field models relevant to spatial representations, and may inform biomimetic approaches to spatial representation and navigation. Full article

Visual mental imagery, the ability to generate and manipulate internal visual experiences without direct sensory input, links perception with memory, planning, and higher cognition. In this targeted narrative review, we synthesize neuroimaging and lesion evidence on the brain basis of visual imagery, with a focus on neuroradiological correlates of the ventral and dorsal visual pathways. Unlike prior cognitive neuroscience reviews that primarily emphasize functional mechanisms, this review is neuroradiology-oriented and integrates lesion patterns and white-matter disconnection to support clinico-radiological interpretation of imagery complaints. Using a dual-stream framework, we contrast ventral occipito-temporal systems that preferentially support object imagery (appearance-based features such as form, faces/objects, and color, with texture remaining under-studied) with dorsal occipito-parietal systems that preferentially support spatial imagery (relations, transformations, and navigation). Across studies, imagery recruitment is strongly task- and stage-dependent: ventral regions are most often engaged during object-focused imagery, whereas parietal regions are prominent during spatial transformation tasks, with evidence for interaction between pathways when demands require both content and spatial operations. Structural and clinico-radiological findings indicate that imagery impairment can arise from focal posterior lesions and posterior neurodegenerative syndromes but also from network disruption affecting long-range connections that support top-down access to posterior representations. Finally, emerging work on aphantasia and hyperphantasia supports a network-level view in which imagery vividness relates to how effectively higher-order systems engage visual representations. We conclude that standardized, stream-sensitive tasks and multimodal approaches combining functional and structural imaging with lesion-based evidence are key to discovering clinically actionable biomarkers of imagery dysfunction. Full article

Effective rehabilitation tools are essential for improving language outcomes in chronic aphasia. Speech entrainment is a behavioral treatment that has shown promise in enhancing speech output in nonfluent aphasia, potentially by acting as an external mechanism to synchronize anterior and posterior language regions in the left hemisphere. Transcranial alternating current stimulation has been hypothesized to enhance functional connectivity between brain regions by amplifying endogenous oscillations. This proof-of-concept study explored whether high-definition tACS (HD-tACS) could improve speech fluency in nonfluent aphasia when paired with speech entrainment. In a double-blind, pseudorandomized study, 1 mA of HD-tACS at 7 Hz was applied to anterior and posterior left-hemisphere regions of individuals with nonfluent aphasia (N = 13). Stimulation was applied under three conditions: in-phase, anti-phase, and sham, and paired speech entrainment. Three outcome measures were examined: (1) number of words produced; (2) number of errors, and (3) ‘entrainment’ to the speech entrainment model. Group-level analyses for two of the three outcome measures reveal statistically significant differences between the experimental conditions. In-phase alternating current stimulation yielded more words and better entrainment to the audiovisual model than the sham condition. This study provides promising evidence that HD-tACS could improve speech production in individuals with nonfluent aphasia. These results contribute to growing evidence supporting the therapeutic potential of non-invasive brain stimulation approaches as an adjuvant to traditional behavioral speech-language therapy in stroke survivors. Full article

Background: Against the backdrop of global population aging, understanding the mechanisms of age-related cognitive decline has become crucial for improving the health and quality of life in older adults. Methods: This study employed a multimodal approach to investigate the neural modulations induced by a motor cognitive dual task and their relationship with age-related decline. By integrating behavioral assessments, electroencephalography (EEG), and body composition analysis, we comprehensively evaluated performance and neural correlates in 19 younger and 18 older adults. Specifically, EEG analyses focused on comparing pre-task and post-task resting-state recordings to investigate the immediate impact of a single acute cognitive-motor dual-task session on neural oscillations and brain network organization. Results: Key findings include: (1) older adults exhibited significantly inferior performance in task accuracy, reaction time, and composite performance score compared to younger adults (p < 0.001); (2) neural oscillatory analysis of resting-state data revealed a localized increase in gamma-band power at posterior-temporal sites (PO4/T6) in older adults following the dual-task, while younger adults exhibited widespread multi-band (delta to beta) power modulation across frontal, central, and temporal regions in younger adults; (3) brain network analysis demonstrated synergistic enhancement of multi-band (Theta, Alpha, Beta, Gamma) connectivity and optimized topological organization in younger adults post-task, contrasting with network rigidity and localized compensatory patterns in older adults; (4) correlation analyses indicated significant associations between dual-task performance and MoCA-B scores in older adults (r = 0.861, p < 0.001). Conclusions: This study innovatively elucidates the neurophysiological characteristics of brain aging. The motor-cognitive dual-task paradigm proves to be a sensitive tool for capturing early cognitive changes, holding significant promise for clinical screening. Full article

Background/Objectives: The global incidence of diabetes in childhood is increasing, raising concern about its long-term effects on the developing brain. Although paediatric diabetes research has traditionally focused on microvascular and macrovascular complications, accumulating evidence indicates that the brain is also a vulnerable target. Methods: This narrative review synthesizes current knowledge on the impact of diabetes on brain health in children and adolescents, with emphasis on epidemiology, neuroimaging and cognitive outcomes, underlying mechanisms, risk and protective factors, and clinical implications. Results: In type 1 diabetes (T1D), studies consistently demonstrate subtle but measurable alterations in brain structure, including reduced growth of total, grey, and white matter volumes, alongside functional and microstructural changes. These neurobiological differences are associated with mild deficits in cognition, particularly in attention, executive function, memory, and processing speed. While clinically significant impairment affects a minority, subclinical alterations are common and may accumulate over time. Key risk factors include chronic hyperglycaemia, glycaemic variability, severe hypoglycaemia, diabetic ketoacidosis, and younger age at onset, whereas good glycaemic stability, diabetes technologies, supportive psychosocial environments, and adequate sleep appear protective. Proposed mechanisms involve oxidative stress, neuroinflammation, disrupted insulin signalling, altered cerebral metabolism, and vulnerability of the immature brain during critical developmental windows. Type 2 diabetes (T2D), increasingly diagnosed in youth, is also associated with adverse brain outcomes. Emerging data link early-onset T2D to alterations in brain structure and connectivity, poorer cognitive performance, and increased mental health burden, mediated by hyperglycaemia, insulin resistance, inflammation, and psychosocial stressors. Conclusions: Overall, childhood diabetes—both T1D and T2D—is associated with meaningful effects on brain development and function. Longitudinal and interventional studies are needed to establish causality and determine whether optimizing glycaemic control and psychosocial support can mitigate neurocognitive risk. Recognizing brain health as a potential complication of paediatric diabetes has important implications for monitoring, prevention, and clinical care. Full article

Impaired blood–brain barrier (BBB) integrity is a common hallmark of neurological disorders associated with neuroinflammation, neurodegeneration and aging. The function of the BBB relies heavily on the interaction between astrocytes and endothelial cells, the most closely connected elements of the neurovascular unit. Under inflammatory conditions, astrocytes can undergo a range of metabolic changes, becoming pro-inflammatory and harmful to endothelial cells. Upon activation, astrocytes secrete a plethora of inflammatory mediators that severely disrupt the barrier function of the BBB. ω-3 polyunsaturated fatty acids (PUFAs), mainly docosahexaenoic and eicosapentaenoic acids, exhibit protective anti-inflammatory and antioxidant effects demonstrated in various neurological disorders. This review focused on the role of ω-3 PUFAs and their oxidative derivatives, specialized pro-resolving mediators, in preserving the BBB’s integrity via suppression of astrocytes’ activation or even promotion of their transition from an A1 to an A2 phenotype. We considered mainstream mechanisms of the anti-inflammatory and antioxidant effects of ω-3 PUFAs on reactive astrocytes, such as stimulation of the Nrf2/ARE and Wnt/β-catenin signaling pathways, inhibition of NF-κB/matrix metalloproteinase activity and the JAK/STAT3 signaling axis, as well as the contribution of ω-3 PUFA-activated GPCRs and PPAR transcriptional factors, particularly regarding the role of these mechanisms in preserving the BBB’s integrity. Full article

Motor recovery after stroke, spinal cord injury, or traumatic brain injury reflects relearning rather than simple restitution, as surviving circuits retain plastic potential that can be re-engaged through temporally precise stimulation. This review synthesizes convergent findings demonstrating that Hebbian and spike-timing-dependent mechanisms govern reorganization across cortical, striatal, and spinal levels. Leveraging these timing rules to shape excitability during receptive network states enables durable changes in connectivity and behavior. This effect depends on temporal precision, physiological state, and reinforcement—not stimulus intensity alone—within plasticity windows regulated by metaplastic mechanisms that determine whether Hebbian processes are expressed. Together, these principles define a translational framework for neurorehabilitation, emphasizing biomarker-guided, adaptive, and scalable strategies aligned with intrinsic rules of experience-dependent reorganization. Full article

The development of the human brain starts with the orchestrated expression of our genes during embryogenesis. Non-protein-coding DNA sequences (gene promoters and enhancers) dynamically interact to form a three-dimensional (3D) network, orchestrating gene expression. We discuss novel perspectives on how DNA sequence variants within regulatory DNA, identified by whole-genome sequencing (WGS), contribute to the development of neurodevelopmental disorders (NDDs), including autism spectrum disorders (ASDs). We discuss two recent models explaining the evolution of a subset of regulatory sequences, Human Accelerated DNA Regions (HARs), proposed to be involved in the evolution of uniquely human brain features through their participation in the 3D interactions network. We connect this with the recent proposal that rare, recessive inherited sequence variants within HARs, interacting with distant target genes in neural cells, represent risk factors for the development of ASDs. The SOX2 transcription factor, whose heterozygous mutation causes NDDs, shapes the noncoding-DNA interaction network in neural cells, and binds DNA together with FOS, whose recognition sequence is enriched within HARs carrying human-specific substitutions modulating enhancer activity. SOX2 also binds regulatory regions (including HARs) carrying ASD-associated mutations. We highlight research directions based on these findings, which will hopefully improve our understanding of the connection between SOX2-dependent gene regulatory networks, NDDs, and brain evolution. Full article

Background/Objectives: Young adulthood is a critical developmental period during which lifestyle behaviors may shape intrinsic brain network dynamics that support cognition. This pilot longitudinal intervention study examined whether variability in physical activity and sedentary behavior during an 8-week exercise and/or cognitive intervention protocol was associated with changes in intrinsic brain dynamics and cognitive and mood outcomes in undergraduate young adults. Methods: Participants (n = 32) completed resting-state functional magnetic resonance imaging (rs-fMRI) at baseline (T1) and post-intervention (T2). Dynamic functional network connectivity (dFNC) was estimated from 53 intrinsic connectivity networks derived using spatially constrained independent component analysis (ICA). Ten recurring dynamic connectivity states were identified and individualized using constrained dynamic double functional independent primitives (c-ddFIPs). State occupancy and dynamic convergence and divergence metrics were computed to characterize network flexibility. Results: Greater moderate-to-vigorous physical activity was modestly but consistently associated with increased occupancy of integrative higher-order states, particularly States 6 and 7, and reduced occupancy of more segregated configurations. More physically active individuals also demonstrated greater divergence between integrative and low-engagement states, whereas greater sedentary time corresponded to increased similarity among segregated configurations. Working memory performance showed parallel associations with more integrative and better-differentiated dynamic patterns. Conclusions: These findings suggest that dynamic functional network reconfiguration may represent a neurobiological mechanism linking lifestyle behaviors and cognitive health in young adulthood. Furthermore, they highlight the translational promise of engagement-driven, low-burden programs for college-aged young adults, showing that even modest variability in habitual physical activity corresponds to greater engagement and differentiation of integrative connectivity states linked to executive and broader cognitive functions. Full article

Background: The generation of synthetic CT images from MRI scans represents a crucial step toward enabling MRI-only clinical workflows and supporting multi-modal integration in medical imaging, particularly in radiotherapy planning. Despite significant advancements in deep learning models, many current methods still struggle to reconstruct high-density structures, especially bone, and exhibit limited accuracy in density values. This shortcoming is largely attributed to the passage of excessive or noisy features through skip connections in the traditional U-Net architecture, which degrade the quality of information transmitted to the decoder, negatively impacting the clarity of anatomical boundaries and the pixel-wise accuracy of the resulting synthetic image. Methods: In this work, we propose an enhanced 3D U-Net architecture in which the Convolutional Block Attention Module (CBAM) is systematically integrated within each skip connection. The CBAM sequentially applies channel and spatial attention to adaptively reweight encoder feature maps before fusion with the decoder, thereby emphasizing anatomically relevant structures while suppressing irrelevant feature propagation. The model was trained and evaluated on the SynthRAD2023 (Task 1—Brain) MRI–CT dataset. To rigorously assess the contribution of the attention mechanism, a dedicated ablation study was conducted comparing three variants: 3D U-Net with Squeeze-and-Excitation (SE), Coordinate Attention (CA), and the proposed CBAM module. Performance was evaluated using Mean Absolute Error (MAE), Root Mean Square Error (RMSE), Peak Signal-to-Noise Ratio (PSNR), Structural Similarity Index (SSIM), and Normalized Cross-Correlation (NCC). Results: The ablation study demonstrated that the CBAM-enhanced model consistently outperformed both SE- and CA-based variants across all quantitative metrics. Specifically, the proposed method achieved an MAE of $38.2\pm 5.4$ HU and an RMSE of $51.0\pm 12.0$ HU, representing the lowest reconstruction errors among the evaluated models. In addition, it obtained a PSNR of $29.45\pm 2.10$ dB, SSIM of $0.940\pm 0.031$, and NCC of $0.967\pm 0.015$, indicating superior structural preservation and strong voxel-wise correspondence between synthesized and reference CT volumes. These results confirm that the sequential integration of channel and spatial attention provides a statistically and practically meaningful improvement for high-fidelity MRI-to-CT synthesis. Conclusions: Generating high-resolution brain CT images from brain MRI scans using a 3D U-Net network enhanced with a CBAM module can contribute to supporting the clinical workflow by providing additional diagnostic data without the need for extra radiological examinations, thereby enhancing diagnostic efficiency and reducing radiation exposure. This technique helps reduce patient exposure to radiation and improves accessibility in resource-limited settings. Furthermore, this method is valuable for retrospective studies, surgical planning, and image-guided therapy, where complete multi-modal data may not always be available. Full article

Functional near-infrared spectroscopy (fNIRS) is a valuable non-invasive modality for brain-computer interfaces (BCIs), but robust signal interpretation is challenged by the significant temporal variability of the hemodynamic response. Standard linear methods, such as Pearson correlation, often fail to capture functional connectivity when signals exhibit temporal jitter. This study validates an unsupervised Dynamic Time Warping (DTW) clustering framework to robustly identify motor networks from fNIRS data by accommodating non-linear temporal shifts. We analyzed a public fNIRS dataset (N = 30) across right-hand (RHT), left-hand (LHT), and foot tapping (FT) tasks. A robust preprocessing pipeline was implemented, including Wavelet Motion Correction and Common Average Referencing (CAR) to remove artifacts and global systemic noise. The core method involved computing Z-score normalized DTW distance matrices, followed by hierarchical clustering. To validate the framework, we benchmarked it against a standard Pearson Correlation method. Results show that the unsupervised DTW framework achieved a network identification accuracy of 53.17%, significantly outperforming the standard Pearson correlation benchmark (48.06%) with a statistically significant difference (p < 0.05). The framework successfully detected distinct, somatotopically correct modulations: superior-medial activation during foot tapping and lateralized activation during hand tapping. These findings demonstrate that unsupervised DTW clustering is a robust, data-driven approach that outperforms conventional linear methods in capturing functional networks during motor tasks, showing significant potential for next-generation asynchronous BCIs. Full article

Background: Previous research has found that mindfulness-based techniques are beneficial for reducing stress in heavy-drinking individuals. However, the underlying neurobiology of these stress-reducing effects are unclear. Moreover, much of the research examining neurobiological correlates of mindfulness has used static functional connectivity, suggesting that brain activity goes unchanged for the entire length of an MRI scan. Methods: In the current study, we used a state-based dynamic functional connectivity model to examine brain states during either a 10 min mindfulness session or resting control that followed an individually tailored stress imagery task. Using a hidden semi-Markov model (HSMM), six brain states and the associated dynamics of state traversal were estimated for a population of moderate-to-heavy drinkers (N = 32). We modeled the 36 Schaefer atlas regions spanning the salience and default mode networks, and the HSMM characterized each state by its distinct multivariate pattern of activity and covariance structure. Group differences in dwell times, transition behavior, and overall state dynamics were evaluated using permutation tests and mixed-effects models. Results: Participants that experienced the mindfulness session had more transitions and longer time spent in states in which the salience network was more active. Participants assigned to the control group had more transitions and increased time spent in states in which nodes of the default mode network were more active. Moreover, for control participants, increased occupancy time to SN-dominant states was associated with lower perceived stress. Conclusions: Using HSMM provided a unique insight into network connectivity during mindful states; we believe it offers a novel approach to testing and optimizing mindful-based therapies. Full article

Listeria monocytogenes (Lm) is a foodborne pathogen whose virulence depends on the coordinated action of multiple virulence factors. Although deletion of either LIPI-4 or inlB reduces the virulence of Listeria monocytogenes, it remains unknown whether these two factors are functionally or regulatory connected. Therefore, we constructed an inlB deletion mutant and its complemented strain in the Lm928 and ΔLIPI-4 backgrounds. We assessed bacterial growth, biofilm formation, motility, host cell interactions (adhesion, invasion, intracellular proliferation), plaque formation, mouse organ colonization. Growth curve analysis showed no significant differences among strains. qPCR revealed that LIPI-4 modulates inlB expression in a cell-type-specific manner: inlB was downregulated in ΔLIPI-4 under culture and HTR-8 infection, but upregulated during hCMEC/D3 infection—yet functional defects persisted in all cases. Biofilm assays showed that ΔLIPI-4 and the double mutant exhibited enhanced biofilm formation, with the double mutant exceeding ΔLIPI-4, demonstrating synergistic enhancement. Motility assays indicated that LIPI-4 dominates bacterial movement, with ΔLIPI-4 and the double mutant showing identical severe defects. Plaque formation analysis showed that LIPI-4 is essential for cell-to-cell spread, while inlB deletion unexpectedly enhanced plaque formation—an effect completely abolished in the absence of LIPI-4. Host cell assays across Caco-2, HTR-8, and hCMEC/D3 models revealed that LIPI-4 is the core determinant of adhesion, invasion, and intracellular proliferation, whereas inlB contributes in the context of LIPI-4 and its effects vary with the specific cellular process examined. In mice, LIPI-4 was essential for systemic colonization of the liver and spleen, with inlB acting as a co-factor, whereas inlB unexpectedly promoted higher bacterial burdens in the brain, suggesting that inlB modulates LIPI-4-mediated neuroinvasion. Overall, our results establish LIPI-4 as the central determinant of Lm virulence, with inlB acting as a context-dependent co-factor that modulates LIPI-4-mediated pathogenesis in a cell type- and tissue-specific manner. Full article

Stroke remains a leading cause of death and disability worldwide, imposing significant burdens on patients, families, and healthcare systems. Despite advances in acute management and rehabilitation, effective interventions to promote neural recovery remain limited. Hyperbaric oxygen therapy (HBOT) has emerged as a potential adjunctive treatment, but its effects on cortical functional activity—particularly the neurophysiological mechanisms underlying clinical improvements—remain insufficiently understood. This study aimed to investigate the effects of hyperbaric oxygen therapy (HBOT) on cerebral activation in stroke patients using functional near-infrared spectroscopy (fNIRS) and to evaluate its therapeutic efficacy. A total of 23 patients with intracerebral hemorrhage and 20 with cerebral infarction were enrolled. fNIRS data were collected before HBOT and within 10–30 min after treatment completion. During data acquisition, participants performed an alternating left- and right-hand grip task while wearing the fNIRS device throughout the procedure. Changes in near-infrared light intensity were monitored to objectively reflect cortical activity. The results showed that after HBOT, activation patterns in relevant brain regions during the grip task were significantly altered: activation channels during the bilateral grip task changed in cerebral infarction patients, with some brain regions overlapping with those observed in intracerebral hemorrhage patients. In intracerebral hemorrhage patients, the number of significantly activated channels decreased during the left-hand grip task but increased notably during the right-hand grip task, which may be related to cerebral functional compensation and right-hand dominance. Clinical assessments revealed significant post-treatment improvements in Brunnstrom stage, Fugl-Meyer scores, and activities of daily living. These findings suggest that HBOT may contribute to multifaceted recovery of brain function in stroke patients, not only by enhancing cerebral blood flow and oxygenation but also by facilitating neural repair and regeneration, as well as optimizing cerebral activation and functional connectivity. Thus, this study provides an objective basis for understanding the mechanisms and efficacy of HBOT in stroke rehabilitation. Full article