Search Results (98)

Olfactory impairment was assessed in akinetic-rigid (PD_AR) and tremor-predominant (PD_T) subtypes of Parkinson’s disease (PD), classified based on motor symptoms. Seventeen PD_AR, fifteen PD_T, and twenty-four cognitively normal (CN) participants completed the University of Pennsylvania Smell Identification Test (UPSIT). Groups were well-matched for age and demographic variables, with cognitive performance statistically controlled. Resting-state fMRI (rs-fMRI) and seed-based functional connectivity (FC) analyses were conducted to characterize olfactory network (ON) connectivity across groups. UPSIT scores were significantly lower in PD_AR compared to PD_T. Consistently, ON FC values were reduced in PD_AR relative to both PD_T and CN. FC of the primary olfactory cortex (POC) significantly differed between CN and the PD subtypes. Furthermore, connectivity in the orbitofrontal cortex and insula showed significant differences between PD_AR and PD_T, as well as between PD_AR and CN. Notably, ON FC between the left hippocampus and the posterior cingulate cortex (PCC) also differed significantly between PD_AR and PD_T. These findings reveal distinct ON FC patterns across PD_AR and PD_T subtypes. Variations in UPSIT scores suggest that motor symptom subtype is associated with olfactory performance. Moreover, ON connectivity closely paralleled the UPSIT scores, reinforcing a neural basis for olfactory deficits in PD. Given the accelerated motor and cognitive decline often observed in the PD_AR, these results support the potential of olfactory impairment as a clinical marker for disease severity. Full article

Background/Objectives: Olfactory impairment has been proposed as an early marker for Alzheimer’s disease (AD), yet the mechanisms linking sensory decline to genetic and environmental risk factors remain unclear. We aimed to identify early biomarkers and brain network alterations associated with AD risk by multimodal analyses in humanized APOE mice. Methods: We evaluated olfactory behavior, diffusion MRI connectomics, and brain and blood transcriptomics in mice stratified by APOE2, APOE3, and APOE4 genotypes, age, sex, high-fat diet, and immune background (HN). Behavioral assays assessed odor salience, novelty detection, and memory. Elastic Net-regularized multi-set canonical correlation analysis (MCCA) was used to link behavior to brain connectivity. Blood transcriptomics and gene ontology analyses identified peripheral molecular correlates. Results: APOE4 mice exhibited accelerated deficits in odor-guided behavior and memory, especially under high-fat diet, while APOE2 mice were more resilient (ANOVA: APOE x HN, F(2, 1669) = 77.25, p < 0.001, eta squared = 0.08). Age and diet compounded behavioral impairments (diet x age: F(1, 1669) = 16.04, p < 0.001). Long-term memory was particularly reduced in APOE4 mice (APOE x HN, F(2,395) = 5.6, p = 0.004). MCCA identified subnetworks explaining up to 24% of behavioral variance (sum of canonical correlations: 1.27, 95% CI [1.18, 1.85], p < 0.0001), with key connections involving the ventral orbital and somatosensory cortices. Blood eigengene modules correlated with imaging changes (e.g., subiculum diffusivity: r = −0.5, p < 1 × 10⁻³⁰), and enriched synaptic pathways were identified across brain and blood. Conclusions: Olfactory behavior, shaped by genetic and environmental factors, may serve as a sensitive, translatable biomarker of AD risk. Integrative systems-level approaches reveal brain and blood signatures of early sensory–cognitive vulnerability, supporting new avenues for early detection and intervention in AD. Full article

Threshold-switching memristors (TSMs) are emerging as key enablers for hardware spiking neural networks, offering intrinsic spiking dynamics, sub-pJ energy consumption, and nanoscale footprints ideal for brain-inspired computing at the edge. This review provides a comprehensive examination of how TSMs emulate diverse spiking behaviors—including oscillatory, leaky integrate-and-fire (LIF), Hodgkin–Huxley (H-H), and stochastic dynamics—and how these features enable compact, energy-efficient neuromorphic systems. We analyze the physical switching mechanisms of redox and Mott-type TSMs, discuss their voltage-dependent dynamics, and assess their suitability for spike generation. We review memristor-based neuron circuits regarding architectures, materials, and key performance metrics. At the system level, we summarize bio-inspired neuromorphic platforms integrating TSM neurons with visual, tactile, thermal, and olfactory sensors, achieving real-time edge computation with high accuracy and low power. Finally, we critically examine key challenges—such as stochastic switching origins, device variability, and endurance limits—and propose future directions toward reconfigurable, robust, and scalable memristive neuromorphic architectures. Full article

Zeugodacus cucuribitae (Coquillett) (Z. cucuribitae) is a global extremely invasive quarantine pest which has a wide host range of fruits and vegetables. At present, there are a few control measures for Z. cucuribitae, and deltamethrin and avermectin are commonly used. Among the hosts of Z. cucuribitae, Luffa acutangular, Luffa cylindrica, Sechium edule, Brassica oleracea var. botrytis, Musa nana, and Fragaria × ananassa are non-favored hosts. However, it is still not clear why these hosts are non-favored and whether there are any repellent components of Z. cucuribitae in these hosts. In this study, the components of these six hosts were collected from the literature, and the genes of odor and chemical sensation were determined from the genome of Z. cucuribitae. After the potential relationships between these components and genes were determined by molecular docking methods, the KEGG and GO enrichment analysis of these genes was conducted, and a complex network of genes vs. components vs. Kegg pathway vs. GO terms was constructed and used to select the key components for experiments. The results show that oleanolic acid (1 mg/mL, 0.1 mg/mL, and 0.01 mg/mL), rotenone (1 mg/mL, 0.1 mg/mL, and 0.01 mg/mL), and beta-caryophyllene oxide (1 mg/mL, 0.1 mg/mL, and 0.01 mg/mL) had a significant repellent effect on Z. cucuribitae, and three components, rotenone (1 mg/mL and 0.1 mg/mL), echinocystic acid (1 mg/mL, 0.1 mg/mL, and 0.01 mg/mL), and beta-caryophyllene oxide (1 mg/mL, and 0.1 mg/mL) had significant stomach toxicity in Z. cucuribitae. Furthermore, a complex signaling pathway was built and used to predict the effect of these components on Z. cucuribitae. These components probably play roles in the neuroactive ligand–receptor interaction (ko04080) and calcium signaling (ko04020) pathways. This study provides a reference for the prevention and control of Z. cucuribitae and a scientific reference for the rapid screening and development of new pest control drugs. Full article

Background: Olfactory dysfunction (OD)—including anosmia and hyposmia—is a common and often persistent outcome of viral infections. This systematic review consolidates findings from structural and functional MRI studies to explore how COVID-19 SARS-CoV-2-induced smell loss alters the brain. Considerable heterogeneity was observed across studies, influenced by differences in methodology, population characteristics, imaging timelines, and OD classification. Methods: Following PRISMA guidelines, we conducted a systematic search of PubMed/MEDLINE, Scopus, and Web of Science to identify MRI-based studies examining COVID-19’s SARS-CoV-2 OD. Twenty-four studies were included and categorized based on imaging focus: (1) olfactory bulb (OB), (2) olfactory sulcus (OS), (3) grey and white matter changes, (4) task-based brain activation, and (5) resting-state functional connectivity. Demographic and imaging data were extracted and analyzed accordingly. Results: Structural imaging revealed consistent reductions in olfactory bulb volume (OBV) and olfactory sulcus depth (OSD), especially among individuals with OD persisting beyond three months, suggestive of inflammation and neurodegeneration in olfactory-associated regions like the orbitofrontal cortex and thalamus. Functional MRI studies showed increased connectivity in early-stage OD within regions such as the piriform and orbitofrontal cortices, possibly reflecting compensatory activity. In contrast, prolonged OD was associated with reduced activation and diminished connectivity, indicating a decline in olfactory processing capacity. Disruptions in the default mode network (DMN) and limbic areas further point to secondary cognitive and emotional effects. Diffusion tensor imaging (DTI) findings—such as decreased fractional anisotropy (FA) and increased mean diffusivity (MD)—highlight white matter microstructural compromise in individuals with long-term OD. Conclusions: COVID-19’s SARS-CoV-2 olfactory dysfunction is associated with a range of cerebral alterations that evolve with the duration and severity of smell loss. Persistent dysfunction correlates with greater neural damage, underscoring the need for longitudinal neuroimaging studies to better understand recovery dynamics and guide therapeutic strategies. Full article

Background/Objectives: Major Depression (MD) is a common disorder that has significant social and economic impacts. Approximately 30% of all MD patients are refractory to common treatments, representing a major obstacle to managing the impacts of depression. One potential explanation for the incomplete treatment efficacy in MD is a substantial divergence in the mechanisms and brain networks involved in different subtypes of the disorder. The aim of this study was to identify novel brain regional targets for MD clinical screening using a gene-informed approach. Methods: A new analysis pipeline, called “Analysis Tool for Local Association of Neuronal Transcript Expression” (ATLANTE), was generated and validated. The pipeline identifies brain regions based on the shared high expression of user-generated gene lists; in this study, the pipeline was applied to discover brain regions that may be significant to MD. Results: Nine discrete brain regions of interest to MD were identified, including the temporal pole, anterior transverse temporal gyrus (Heschl’s gyrus), olfactory tubercle, ventral tegmental area, postcentral gyrus, CA1 of the hippocampus, olfactory area, perirhinal gyrus, and posterior insular cortex. The application of network and clustering analyses identified genes of special importance, including, most notably, PRKN. Conclusions: This study provides two major insights. The first is that several brain regions have unique MD-associated genetic architectures, indicating a potential explanation for subtype-specific dysfunction. The second insight is that the PRKN gene, which is strongly associated with Parkinson’s disease, is a key player amongst the MD-associated genes. These findings reveal novel targets for the clinical screening of depression and reinforce a mechanistic connection between MD and Parkinson’s disease. Full article

Background: Membranous nephropathy (MN), a prevalent glomerular disorder, remains poorly understood in terms of its association with mitochondrial dynamics (MD). This study investigated the mechanistic involvement of mitochondrial dynamics-related genes (MDGs) in the pathogenesis of MN. Methods: Comprehensive bioinformatics analyses—encompassing Mendelian randomization, machine-learning algorithms, and single-cell RNA sequencing (scRNA-seq)—were employed to interrogate transcriptomic datasets (GSE200828, GSE73953, and GSE241302). Core MDGs were further validated using reverse-transcription quantitative polymerase chain reaction (RT-qPCR). Results: Four key MDGs—RTTN, MYO9A, USP40, and NFKBIZ—emerged as critical determinants, predominantly enriched in olfactory transduction pathways. A nomogram model exhibited exceptional diagnostic performance (area under the curve [AUC] = 1). Seventeen immune cell subsets, including regulatory T cells and activated dendritic cells, demonstrated significant differential infiltration in MN. Regulatory network analyses revealed ATF2 co-regulation mediated by RTTN and MYO9A, along with RTTN-driven modulation of ELOA-AS1 via hsa-mir-431-5p. scRNA-seq analysis identified mesenchymal–epithelial transitioning cells as key contributors, with pseudotime trajectory mapping indicating distinct temporal expression profiles: NFKBIZ (initial upregulation followed by decline), USP40 (gradual fluctuation), and RTTN (persistently low expression). RT-qPCR results corroborated a significant downregulation of all four genes in MN samples compared to controls (p < 0.05). Conclusions: These findings elucidate the molecular underpinnings of MDG-mediated mechanisms in MN, revealing novel diagnostic biomarkers and therapeutic targets. The data underscore the interplay between mitochondrial dynamics and immune dysregulation in MN progression, providing a foundation for precision medicine strategies. Full article

Both voluntary mental imagery and dream imagery involve multisensory representations without externally present stimuli that can be categorized as offline perceptions. Due to common mechanisms, correlations between multisensory dream imagery profiles and multisensory voluntary mental imagery profiles were hypothesized. In a sample of 226 participants, correlations within the respective state of consciousness were significantly bigger than across, favouring two distinct networks. However, the association between the vividness of voluntary mental imagery and vividness of dream imagery was moderated by the frequency of dream recall and lucid dreaming, suggesting that both networks become increasingly similar when higher metacognition is involved. Additionally, the vividness of emotional and visual imagery was significantly higher for dream imagery than for voluntary mental imagery, reflecting the immersive nature of dreams and the continuity of visual dominance while being awake and asleep. In contrast, the vividness of auditory, olfactory, gustatory, and tactile imagery was higher for voluntary mental imagery, probably due to higher cognitive control while being awake. Most results were replicated four weeks later, weakening the notion of state influences. Overall, our results indicate similarities between dream imagery and voluntary mental imagery that justify a common classification as offline perception, but also highlight important differences. Full article

The integration of intermittent wind power into modern grids necessitates highly accurate forecasting models to ensure stability and efficiency. To address the limitations of traditional backpropagation (BP) neural networks, such as slow convergence and susceptibility to local optima, this study proposes a novel hybrid framework: the Multi-Strategy Coati Optimization Algorithm (SZCOA)-optimized BP neural network (SZCOA-BP). The SZCOA integrates three innovative strategies—a population position update mechanism for global exploration, an olfactory tracing strategy to evade local optima, and a soft frost search strategy for refined exploitation—to enhance the optimization efficiency and robustness of BP networks. Evaluated on the CEC2017 benchmark, the SZCOA outperformed state-of-the-art algorithms, including ICOA, DBO, and PSO, achieving superior convergence speed and solution accuracy. Applied to a real-world wind power dataset (912 samples from Alibaba Cloud Tianchi), the SZCOA-BP model attained an R² of 94.437% and reduced the MAE to 10.948, significantly surpassing the standard BP model (R²: 81.167%, MAE: 18.891). Comparative analyses with COA-BP, BWO-BP, and other hybrid models further validated its dominance in prediction accuracy and stability. The proposed framework not only advances wind power forecasting but also offers a scalable solution for optimizing complex renewable energy systems, supporting global efforts toward sustainable energy transitions. Full article

Background/Objectives: Olfaction is in many ways the least understood sensory modality. Its organization and connectivity are still under debate. The aim of this study was to investigate the anatomy of the olfactory system by using a cadaver fiber dissection technique and in vivo tractography to attain a deeper understanding of the subcortical connectivity and organization. Methods: Ten cerebral hemispheres were used in this study for white matter dissection according to Klingler’s technique. Measurements of different cortical structures and interhemispheric symmetry were compared. Diffusion tensor imaging sequences from twenty-five healthy individuals from the Human Connectome Project dataset were used to explore the connectivity of the olfactory system using DSI Studio. White matter connectivity between the following were reconstructed in vivo: (1) Olfactory bulb to primary olfactory cortices; (2) Olfactory bulb to secondary olfactory cortices; (3) Primary to secondary olfactory cortices. The DTI metrics of the identified major associative, projection and commissural pathways were subsequently correlated with olfactory function and cognition in seventy-five healthy individuals with Spearman’s rank correlation and the Benjamini–Hochberg method for false discoveries (CI 95%, p < 0.05) using R. Results: 1. The dissection showed that the lateral stria was significantly longer on the left side and projected towards the amygdala, the entorhinal and piriform cortex. 2. The medial stria was not evident as a consistent white matter structure. 3. Both dissection and tractography showed that major associative white matter pathways such as the uncinate fasciculus, the inferior fronto-occipital fasciculus and cingulum supported the connectivity between olfactory areas together with the anterior commissure. 4. No significant correlation was found between DTI metrics and sensory or cognition test results. Conclusions: We present the first combined fiber dissection analysis and tractography of the olfactory system. We propose a novel definition where the primary olfactory network is defined by the olfactory tract/bulb and primary olfactory cortices through the lateral stria only. The uncinate fasciculus, inferior fronto-occipital fasciculus and cingulum are the associative pathways supporting the connectivity between primary and secondary olfactory areas together with the anterior commissure. We suggest considering these structures as a secondary olfactory network. Further work is needed to attain a deeper understanding of the pathological and physiological implications of the olfactory system. Full article

Background: Pain is prevalent in almost all populations and may often hinder visual, auditory, tactile, olfactory, and taste perception as it alters brain neural processing. The quantitative methods emerging to define pain and assess its effects on neural functions and perception are important. Identifying pain biomarkers is one of the initial stages in developing such models and interventions. The existing literature has explored chronic and experimentally induced pain, leveraging electroencephalograms (EEGs) to identify biomarkers and employing various qualitative and quantitative approaches to measure pain. Objectives: This systematic review examines the methods, participant characteristics, types of pain states, associated pain biomarkers of the brain’s electrical activity, and limitations of current pain studies. The review identifies what experimental methods researchers implement to study human pain states compared to human control pain-free states, as well as the limitations in the current techniques of studying human pain states and future directions for research. Methods: The research questions were formed using the Population, Intervention, Comparison, Outcome (PICO) framework. A literature search was conducted using PubMed, PsycINFO, Embase, the Cochrane Library, IEEE Explore, Medline, Scopus, and Web of Science until December 2024, following the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines to obtain relevant studies. The inclusion criteria included studies that focused on pain states and EEG data reporting. The exclusion criteria included studies that used only MEG or fMRI neuroimaging techniques and those that did not focus on the evaluation or assessment of neural markers. Bias risk was determined by the Newcastle–Ottawa Scale. Target data were compared between studies to organize the findings among the reported results. Results: The initial search resulted in 592 articles. After exclusions, 24 studies were included in the review, 6 of which focused on chronic pain populations. Experimentally induced pain methods were identified as techniques that centered on tactile perception: thermal, electrical, mechanical, and chemical. Across both chronic and stimulated pain studies, pain was associated with decreased or slowing peak alpha frequency (PAF). In the chronic pain studies, beta power increases were seen with pain intensity. The functional connectivity and pain networks of chronic pain patients differ from those of healthy controls; this includes the processing of experimental pain. Reportedly small sample sizes, participant comorbidities such as neuropsychiatric disorders and peripheral nerve damage, and uncontrolled studies were the common drawbacks of the studies. Standardizing methods and establishing collaborations to collect open-access comprehensive longitudinal data were identified as necessary future directions to generalize neuro markers of pain. Conclusions: This review presents a variety of experimental setups, participant populations, pain stimulation methods, lack of standardized data analysis methods, supporting and contradicting study findings, limitations, and future directions. Comprehensive studies are needed to understand the pain and brain relationship deeper in order to confirm or disregard the existing findings and to generalize biomarkers across chronic and experimentally induced pain studies. This requires the implementation of larger, diverse cohorts in longitudinal study designs, establishment of procedural standards, and creation of repositories. Additional techniques include the utilization of machine learning and analyzing data from long-term wearable EEG systems. The review protocol is registered on INPLASY (# 202520040). Full article

Modeling the brain dependence network is central to understanding underlying neural mechanisms such as perception, action, and memory. In this study, we present a broad range of statistical methods for analyzing dependence in a brain network. Leveraging a combination of classical and cutting-edge approaches, we analyze multivariate hippocampal local field potential (LFP) time series data concentrating on the encoding of nonspatial olfactory information in rats. We present the strengths and limitations of each method in capturing neural dynamics and connectivity. Our analysis begins with exploratory techniques, including correlation, partial correlation, spectral matrices, and coherence, to establish foundational connectivity insights. We then investigate advanced methods such as Granger causality (GC), robust canonical coherence analysis, spectral transfer entropy (STE), and wavelet coherence to capture dynamic and nonlinear interactions. Additionally, we investigate the utility of topological data analysis (TDA) to extract multi-scale topological features and explore deep learning-based canonical correlation frameworks for connectivity modeling. This comprehensive approach offers an introduction to the state-of-the-art techniques for the analysis of dependence networks, emphasizing the unique strengths of various methodologies, addressing computational challenges, and paving the way for future research. Full article

Electroencephalography (EEG)-basedpersonal identification has gained significant attention, but fluctuations in emotional states often affect model accuracy. Previous studies suggest that multisensory stimuli, such as video and olfactory cues, can enhance emotional responses and improve EEG-based identification accuracy. This study proposes a novel deep learning-based model, CNN-BiLSTM-Residual Network (CBR-Net), for EEG-based identification and establishes a multisensory emotional EEG dataset with both video-only and olfactory-enhanced video stimulation. The model includes a convolutional neural network (CNN) for spatial feature extraction, Bi-LSTM for temporal modeling, residual connections, and a fully connected classification module. Experimental results show that olfactory-enhanced video stimulation significantly improves the emotional intensity of EEG signals, leading to better recognition accuracy. The CBR-Net model outperforms video-only stimulation, achieving the highest accuracy for negative emotions (96.59%), followed by neutral (94.25%) and positive emotions (95.42%). Ablation studies reveal that the Bi-LSTM module is crucial for neutral emotions, while CNN is more effective for positive emotions. Compared to traditional machine learning and existing deep learning models, CBR-Net demonstrates superior performance across all emotional states. In conclusion, CBR-Net enhances identity recognition accuracy and validates the advantages of multisensory stimuli in EEG signals. Full article

Olfaction plays a crucial role in crustaceans for essential activities such as foraging and predator evasion. Among the components involved in olfactory perception, Ionotropic Receptors (IRs) are particularly important. Oratosquilla oratoria, a perennial crustacean of substantial economic and ecological value, serves as an ideal model for studying olfactory mechanisms. Identifying the IR chemosensory genes in O. oratoria enhances our understanding of its olfactory recognition system. Based on the whole-genome data of O. oratoria, we identified and analyzed 50 members of the IR gene family (OratIRs) through bioinformatics approaches. These genes were classified into subfamilies of co-receptor IRs and tuning IRs. The physicochemical properties of the encoded proteins exhibit marked variability, indicating distinct roles. The motif types and conserved domains among these subfamilies display certain similarities, but their gene structures differ markedly. Furthermore, we found that OratIR25a, OratIR07629, and OratIR14286 are key nodes in protein–protein interaction networks, coordinating organisms’ responses to signals like temperature and acids. We utilized fluorescence in situ hybridization (FISH) to find that OratIR75-1 and OratIR8a demonstrated robust expression signals in the antennae of the O. oratoria. These findings lay a foundation for further investigations and elucidate the functional roles of olfactory receptor genes in crustaceans. Full article

Forest environments have been demonstrated to promote human health and well-being through rich sensory experiences. However, the mechanisms by which olfactory experience affects visitors’ mental health remain to be thoroughly researched, and discussions on emotional resilience, a key competency affecting an individual’s mental health, are particularly rare. To address the challenges of high subjectivity, difficulty in quantifying, and high context-dependency of olfactory experience and emotional resilience in such studies, large language models were introduced to study the National Forest Parks in China and analyse massive user-generated data. This provided new possibilities for constructing a more comprehensive theoretical paradigm of olfactory experience–emotional resilience. The findings indicate that olfactory experiences in National Forest Parks exert a substantial influence on tourists’ emotional resilience, with diverse olfactory experiences demonstrating a more pronounced impact on emotional resilience compared to a single type of olfactory experience. However, this impact exhibits an inverted U-shaped relationship. Natural environment olfactory experiences were found to be more conducive to attention restoration, while artificial environment olfactory experiences were more likely to induce nostalgic feelings. This study found that nostalgic feelings significantly mediated the relationship between artificial environment olfactory experience and emotional resilience, while attention restoration did not significantly mediate the relationship between natural environment olfactory experience and emotional resilience. This provides a novel perspective on the examination of the complex relationship between forest environments, olfactory experience, and emotional resilience. Semantic analyses revealed the complexity and network characteristics of olfactory experiences in National Forest Parks, and at the same time identified four main types of olfactory experiences and scenarios. This research offers valuable insights for forest recreation and leisure management, as well as public health policy development. Full article