Human Brain Research Articles

Enhancing EEG data quality and precision for cloud-based clinical applications: an evaluation of the SLOG framework

Automation is revamping our preprocessing pipelines, and accelerating the delivery of personalized digital medicine. It improves efficiency, reduces costs, and allows clinicians to treat patients without significant delays. However, the influx of multimodal data highlights the need to protect sensitive information, such as clinical data, and safeguard data fidelity. One of the neuroimaging modalities that produces large amounts of time-series data is Electroencephalography (EEG). It captures the neural dynamics in a task or resting brain state with high temporal resolution. EEG electrodes placed on the scalp acquire electrical activity from the brain. These electrical potentials attenuate as they cross multiple layers of brain tissue and fluid yielding relatively weaker signals than noise-low signal-to-noise ratio. EEG signals are further distorted by internal physiological artifacts, such as eye movements (EOG) or heartbeat (ECG), and external noise, such as line noise (50 Hz). EOG artifacts, due to their proximity to the frontal brain regions, are particularly challenging to eliminate. Therefore, a widely used EOG rejection method, independent component analysis (ICA), demands manual inspection of the marked EOG components before they are rejected from the EEG data. We underscore the inaccuracy of automatized ICA rejection and provide an auxiliary algorithm-Second Layer Inspection for EOG (SLOG) in the clinical environment. SLOG based on spatial and temporal patterns of eye movements, re-examines the already marked EOG artifacts and confirms no EEG-related activity is mistakenly eliminated in this artifact rejection step. SLOG achieved a 99% precision rate on the simulated dataset while 85% precision on the real EEG dataset. One of the primary considerations for cloud-based applications is operational costs, including computing power. Algorithms like SLOG allow us to maintain data fidelity and precision without overloading the cloud platforms and maxing out our budgets.

Genetic Insights Into Hypothalamic Hamartoma: Unraveling Somatic Variants.

Hypothalamic hamartomas (HHs) are rare developmental brain lesions associated with drug-resistant epilepsy and often subjected to epilepsy surgery. Brain somatic variants in genes affecting the Sonic hedgehog (Shh) and primary cilia signaling pathways have been implicated in approximately 50% of nonsyndromic HH cases. This study aims to characterize a new cohort of 9 HH cases and elucidate their genetic etiology. We recruited 9 HH cases including 8 nonsyndromic cases of which 4 were type IV HH. Genomic DNA was extracted from peripheral blood and surgical brain tissues, and somatic variants were investigated using high-depth whole-exome sequencing. Pathogenic somatic variants in known HH genes (GLI3, OFD1, and PRKACA) were identified in 7 of the 9 cases. In addition, a 2-hit mutational event comprising a germline variant (predicted to impair kinase activity) and a somatic loss-of-heterozygosity was identified in TNK2, a gene encoding a brain-expressed tyrosine kinase. Our findings reinforce the role of somatic variants in Shh and cilia genes in HH cases while also shedding light on TNK2 as a potential novel disease-causing gene. This study emphasizes the increasing importance of brain mosaicism in epilepsy disorders and underscores the critical role of genetic diagnosis derived from resected brain tissue.

Glutathione Therapy in Diseases: Challenges and Potential Solutions for Therapeutic Advancement.

An endogenous antioxidant, reduced glutathione (GSH), is found at high concentrations in nearly all typical cells. GSH synthesis is a controlled process, and any disruption in the process of GSH synthesis could result in GSH depletion. Cellular oxidative damage results from GSH depletion. Various pathological conditions such as aging, cardiovascular disease (CVD), psychiatric disorders, neurological disorders, liver disorders, and diabetes mellitus are more affected by this stress. There are various reasons for GSH reduction, but replenishing it can help to improve this condition. However, there are challenges in this field. Low bioavailability and poor stability of GSH limit its delivery to tissues, mainly brain tissue. Today, new approaches are used for the optimal amount and efficiency of drugs and alternative substances such as GSH. The use of nano-materials and liposomes are effective methods for improving the treatment effects of GSH. The difficulties of GSH decrease and its connection to the most important associated disorders are reviewed for the first time in this essay. The other major concerns are the molecular mechanisms involved in them; the impact of treatment with replacement GSH; the signaling pathways impacted; and the issues with alternative therapies. The utilization of nano-materials and liposomes as potential new approaches to solving these issues is being considered.

CvFormer: Cross-view transFormers with pre-training for fMRI analysis of human brain

In recent years, functional magnetic resonance imaging (fMRI) has been widely utilized to diagnose neurological disease, by exploiting the region of interest (RoI) nodes as well as their connectivities in human brain. However, most of existing works only rely on either RoIs or connectivities, neglecting the potential for complementary information between them. To address this issue, we study how to discover the rich cross-view information in fMRI data of human brain. This paper presents a novel method for cross-view analysis of fMRI data of the human brain, called Cross-view transFormers (CvFormer). CvFormer employs RoI and connectivity encoder modules to generate two separate views of the human brain, represented as RoI and sub-connectivity tokens. Then, basic transformer modules can be used to process the RoI and sub-connectivity tokens, and cross-view modules integrate the complement information across two views. Furthermore, CvFormer uses a global token for each branch as a query to exchange information with other branches in cross-view modules, which only requires linear time for both computational and memory complexity instead of quadratic time. To enhance the robustness of the proposed CvFormer, we propose a two-stage strategy to train its parameters. To be specific, RoI and connectivity views can be firstly utilized as self-supervised information to pre-train the CvFormer by combining it with contrastive learning and then fused to finetune the CvFormer using label information. Experiment results on two public ABIDE and ADNI datasets can show clear improvements by the proposed CvFormer, which can validate its effectiveness and superiority.

Wireless optically pumped magnetometer MEG

The current magnetoencephalography (MEG) systems, which rely on cables for control and signal transmission, do not fully realize the potential of wearable optically pumped magnetometers (OPM). This study presents a significant advancement in wireless OPM-MEG by reducing magnetization in the electronics and developing a tailored wireless communication protocol. Our protocol effectively eliminates electromagnetic interference, particularly in the critical frequency bands of MEG signals, and accurately synchronizes the acquisition and stimulation channels with the host computer's clock. We have successfully achieved single-channel wireless OPM-MEG measurement and demonstrated its reliability by replicating three well-established experiments: The alpha rhythm, auditory evoked field, and steady-state visual evoked field in the human brain. Our prototype wireless OPM-MEG system not only streamlines the measurement process but also represents a major step forward in the development of wearable OPM-MEG applications in both neuroscience and clinical research.

Towards a Systemic Concept of the Brain Ishemia Stroke: Monte Carlo Driven in silico Model.

The work proposes a new mathematical model of dynamic processes of a typical spatially heterogeneous biological system, and sets and solves a mathematical problem of modeling the dynamics of the system of neurovascular units of the brain in conditions of ischemic stroke. There is a description of only a small number of mathematical models of stroke in the literature. This model is being studied and a numerical and software implementation of the corresponding mathematical problem is proposed. This work is the first attempt ever aiming to employ a Monte Carlo computational approach for In Silico simulation of the most critical parameters in molecular and cellular pathogenesis of the brain ischemic stroke. In this work, a new mathematical model of the development of ischemic stroke is proposed in the form of a discrete model based on neurovascular units (NVU) as elements. As a result of testing the program with the assignment of empirically selected coefficients, data were obtained on the evolution of the states of the lattice of the cellular automaton of the model for the spread of stroke in a region of the brain tissue. A resulting new theoretical model of the particular pathologically altered biosystem might be taken as a promising tool for further studies in neurology; general pathology and cell biology. For the first time, a mathematical model has been constructed that allows us to represent the spatial dynamics of the development of the affected area in ischemic stroke of the brain, taking into account neurovascular units as single morphofunctional structures.

Temporal Characterization of Prion Shedding in Secreta of White-Tailed Deer in Longitudinal Study of Chronic Wasting Disease, United States.

Chronic wasting disease (CWD) affects cervids in North America, Asia, and Scandinavia. CWD is unique in its efficient spread, partially because of contact with infectious prions shed in secreta. To assess temporal profiles of CWD prion shedding, we collected saliva, urine, and feces from white-tailed deer for 66 months after exposure to low oral doses of CWD-positive brain tissue or saliva. We analyzed prion seeding activity by using modified amyloid amplification assays incorporating iron oxide bead extraction, which improved CWD detection and reduced false positives. CWD prions were detected in feces, urine, and saliva as early as 6 months postinfection. More frequent and consistent shedding was observed in deer homozygous for glycine at prion protein gene codon 96 than in deer expressing alternate genotypes. Our findings demonstrate that improved amplification methods can be used to identify early antemortem CWD prion shedding, which might aid in disease surveillance of cervids.

Patients with amnestic mild cognitive impairment have higher cerebrovascular impedance than cognitively normal older adults.

Brain hypoperfusion is associated with cognitive impairment. Higher cerebrovascular impedance modulus (Z) may contribute to brain hypoperfusion. We tested hypotheses that patients with amnestic mild cognitive impairment (aMCI) (i.e., those who have a high risk of developing Alzheimer's disease) have higher Z than age-matched cognitively normal individuals, and that high Z is correlated with brain hypoperfusion. Fifty-eight patients with aMCI (67 ± 7 yr) and 25 cognitively normal subjects (CN, 65 ± 6 yr) underwent simultaneous measurements of carotid artery pressure (CAP, via applanation tonometry) and middle cerebral arterial blood velocity (CBV, via transcranial Doppler). Z was quantified using cross-spectral and transfer function analyses between dynamic changes in CBV and CAP. Patients with aMCI exhibited higher Z than NC (1.18 ± 0.34 vs. 1.01 ± 0.35 mmHg/cm/s, P = 0.044) in the frequency range from 0.78 to 4.29 Hz. The averaged Z in the frequency range (0.78-3.13 Hz) of high coherence (>0.9) was inversely correlated with total cerebral blood flow measured with 2-D Doppler ultrasonography normalized by the brain tissue mass (via structural MRI) across both patients with aMCI and NC (r = -0.311, P = 0.007), and in patients with aMCI alone (r = -0.306, P = 0.007). Our findings suggest that patients with aMCI have higher cerebrovascular impedance than cognitively normal older adults and that increased cerebrovascular impedance is associated with brain hypoperfusion.NEW & NOTEWORTHY This is the first study to compare cerebrovascular impedance between patients with amnestic mild cognitive impairment (aMCI) and age-matched cognitively normal individuals. Patients with aMCI had higher cerebrovascular impedance modulus than age-matched cognitively normal individuals, which was correlated with brain hypoperfusion. These results suggest the presence of cerebrovascular dysfunction in the dynamic regulation of cerebral blood flow in older adults who have high risks of Alzheimer's disease.

Tanshinone IIA Against Cerebral Ischemic Stroke and Ischemia-Reperfusion Injury: A Review of the Current Documents.

Stroke is a well-known neurological disorder that carries significant morbidity and mortality rates worldwide. Cerebral Ischemic Stroke (CIS), the most common subtype of stroke, occurs when thrombosis or emboli form elsewhere in the body and travel to the brain, leading to reduced blood perfusion. Cerebral Ischemia/Reperfusion Injury (CIRI) is a common complication of CIS and arises when blood flow is rapidly restored to the brain tissue after a period of ischemia. The therapeutic approaches currently recognized for CIS, such as thrombolysis and thrombectomy, have notable side effects that limit their clinical application. Recently, there has been growing interest among researchers in exploring the potential of herbal agents for treating various disorders and malignancies. One such herbal agent with medicinal applications is tanshinone IIA, an active diterpene quinone extracted from Salvia miltiorrhiza Bunge. Tanshinone IIA has shown several pharmacological benefits, including anti-inflammatory, antioxidant, anti-apoptotic, and neuroprotective properties. Multiple studies have indicated the protective role of tanshinone IIA in CIS and CIRI. This literature review aims to summarize the current findings regarding the molecular mechanisms through which this herbal compound improves CIS and CIRI.

Genome-Wide and Transcriptome-Wide Association Studies on Northern New England and Ohio Amyotrophic Lateral Sclerosis Cohorts.

Amyotrophic lateral sclerosis (ALS) is an age-associated, fatal neurodegenerative disorder causing progressive paralysis and respiratory failure. The genetic architecture of ALS is still largely unknown. We performed a genome-wide association study (GWAS) and transcriptome-wide association study (TWAS) to understand genetic risk factors for ALS using a population-based case-control study of 435 ALS cases and 279 controls from Northern New England and Ohio. Single nucleotide polymorphism (SNP) genotyping was conducted using the Illumina NeuroChip array. Odds ratios were estimated using covariate-adjusted logistic regression. We also performed a genome-wide SNP-smoking interaction screening. TWAS analyses used PrediXcan to estimate associations between predicted gene expression levels across 15 tissues (13 brain tissues, skeletal muscle, and whole blood) and ALS risk. GWAS analyses identified the p.A382T missense variant (rs367543041, p = 3.95E-6) in the TARDBP gene, which has previously been reported in association with increased ALS risk and was found to share a close affinity with the Sardinian haplotype. Both GWAS and TWAS analyses suggested that ZNF235 is associated with decreased ALS risk. Our results support the need for future evaluation to clarify the role of these potential genetic risk factors for ALS and to understand genetic susceptibility to environmental risk factors.

Prediction Models Of The Aphasia Severity After Stroke By Lesion Load Of Cortical Language Areas and White Matter Tracts: An Atlas-based Study.

ObjectiveTo construct relatively objective, atlas-based multivariate models for predicting early aphasia severity after stroke, using structural magnetic resonance imaging. MethodsWe analyzed the clinical and imaging data of 46 patients with post-stroke aphasia. The aphasia severity was identified with a Western Aphasia Battery Aphasia Quotient. The assessments of stroke lesions were indicated by the lesion load of both the cortical language areas (Areas-LL) and four white matter tracts (i.e., the superior longitudinal fasciculus, SLF-LL; the inferior frontal occipital fasciculi, IFOF-LL; the inferior longitudinal, ILF-LL; and the uncinate fasciculi, UF-LL) extracted from human brain atlas. Correlation analyses and multiple linear regression analyses were conducted to evaluate the correlations between demographic, stroke- and lesion-related variables and aphasia severity. The predictive models were then established according to the identified significant variables. Finally, the receiver operating characteristic (ROC) curve was utilized to assess the accuracy of the predictive models. ResultsThe variables including Areas-LL, the SLF-LL, and the IFOF-LL were significantly negatively associated with aphasia severity (p < 0.05). In multiple linear regression analyses, these variables accounted for 59.4% of the variance (p < 0.05). The ROC curve analyses yielded the validated area under the curve (AUC) 0.84 both for Areas-LL and SLF-LL and 0.76 for IFOF-LL, indicating good predictive performance (p < 0.01). Adding the combination of SLF-LL and IFOF-LL to this model increased the explained variance to 62.6% and the AUC to 0.92. ConclusionsThe application of atlas-based multimodal lesion assessment may help predict the aphasia severity after stroke, which needs to be further validated and generalized for the prediction of more outcome measures in populations with various brain injuries.

Evaluating the Efficacy of CortexID Quantitative Analysis in Localization of the Epileptogenic Zone in Patients with Temporal Lobe Epilepsy.

There remains a critical need for precise localization of the epileptogenic foci in individuals with drug-resistant epilepsy (DRE). 18F-Fluorodeoxyglucose positron emission tomography (FDG-PET) imaging can reveal hypometabolic regions during the interval between seizures in patients with epilepsy. However, visual-based qualitative analysis is time-consuming and strongly influenced by physician experience. CortexID Suite is a quantitative analysis software that helps to evaluate PET imaging of the human brain. Therefore, we aimed to evaluate the efficacy of CortexID quantitative analysis in the localization of the epileptogenic zone in patients with temporal lobe epilepsy (TLE). A total of 102 patients with epilepsy who underwent 18F-FDG-PET examinations were included in this retrospective study. The PET visual analysis was interpreted by two nuclear medicine physicians, and the quantitative analysis was performed automatically using CortexID analysis software. The assumed epileptogenic zone was evaluated comprehensively by two skilled neurologists in the preoperative assessment of epilepsy. The accuracy of epileptogenic zone localization in PET visual analysis was compared with that in CortexID quantitative analysis. The diagnostic threshold for the difference in the metabolic Z-score between the right and left sides of medial temporal lobe epilepsy (MTLE) was calculated as 0.87, and that for lateral temporal lobe epilepsy (LTLE) was 2.175. In patients with MTLE, the area under the curve (AUC) was 0.922 for PET visual analysis, 0.853 for CortexID quantitative analysis, and 0.971 for the combined diagnosis. In patients with LTLE, the AUC was 0.842 for PET visual analysis, 0.831 for CortexID quantitative analysis, and 0.897 for the combined diagnosis. These results indicate that the diagnostic efficacy of CortexID quantitative analysis is not inferior to PET visual analysis (p > 0.05), while combined analysis significantly increases diagnostic efficacy (p < 0.05). Among the 23 patients who underwent surgery, the sensitivity and specificity of PET visual analysis for localization were 95.4% and 66.7%, and the sensitivity and specificity of CortexID quantitative analysis were 100% and 50%. The diagnostic efficacy of CortexID quantitative analysis is comparable to PET visual analysis in the localization of the epileptogenic zone in patients with TLE. CortexID quantitative analysis combined with visual analysis can further improve the accuracy of epileptogenic zone localization.

PPARs (Peroxisome Proliferator-activated Receptors) and Their Agonists in Alzheimer's Disease.

Alzheimer's disease (AD) is a neurodegenerative disease leading to dementia because of complex phathomechanisms like amyloid β (Aβ) aggregation, tau aggregates, and neurofibrillary tangles. Peroxisome proliferator-activated receptor (PPAR) agonists have been reported recently with neuroprotective and anti-inflammatory properties. PPARs belong to the superfamily of nuclear hormone receptors and function as ligand-activated transcription factors. These have emerged as crucial players in the pathogenesis of AD. This review presented the potential of PPARs and their agonists in treating neurodegenerative diseases like AD. <P> </P> PPARs regulate the expression of specific genes vital for synaptic function and neurotransmitter release. PPAR agonists play a critical role in increasing the clearance of Aβ peptides by lowdensity lipoprotein receptor-related protein 1 (LRP1) in the microvascular endothelial cells of the human brain. Studies have shown that PPAR agonists reduce the level of APoE-mRNA, contributing to the accumulation of Aβ plaques and up-regulation of PPAR. A knockout of miR-128 has been found to inhibit AD-like cognitive decline, amyloid precursor protein (APP) amyloidogenic processing, and inflammatory responses in AD. <P> </P> PPARs are involved in the pathomechanism of AD, and therefore, PPAR agonists could be viable options for controlling the neurodegenerative symptoms and may be useful in treating AD.

Extracellular vesicle-mediated trafficking of molecular cues during human brain development

Extracellular vesicle-mediated trafficking of molecular cues during human brain development

Evaluation of knowledge of risk factors and warning signs of stroke among paramedical students

Stroke is a medical emergency caused by a blockage or rupture in the blood vessels that supply blood to the brain. This prevents brain tissue from receiving oxygen, leading to the death of brain cells within minutes and causing neurological damage, disability, or death. Aim: The aim of the present study was to assess baseline knowledge regarding stroke risk factors, symptoms, treatment, and information resources. The “golden hour” is a time span of 60 minutes or less after stroke symptoms begin. There are two types of stroke, namely ischemic and hemorrhagic stroke. Ischemic stroke is further divided into thrombotic and embolic stroke. Hemorrhagic stroke is further divided into intracerebral hemorrhage and subarachnoid hemorrhage. Methods: The research method used in the study is a quantitative research approach. Purposive sampling techniques were used and 1050 participants were assessed The questionnaire consists of demographic details such as department, level of education, family history, and knowledge questions based on risk factors and management. Results: This study comprises 1040 patients who fulfill the inclusion criteria. The survey assessed the knowledge of risk factors and warning signs of stroke among future healthcare professionals (pharmacy, nursing, and AHS). The current findings reported that 51.8% of the paramedical students had knowledge about stroke, while the majority of them reported poor knowledge overall. The findings identified that 57.4% of the student population were knowledgeable about risk factors, 69.9% were knowledgeable about warning signs, and 51.8% were knowledgeable about management. These results were similar to many previous studies conducted around the world. Conclusion: Better knowledge about stroke, recognizing the risk factors, and being able to provide immediate management are essential for paramedical students. This is crucial for reducing stroke incidence and improving survival rates of patients by providing better medical help through early detection, rapid intervention, and better long-term health outcomes not only in a medical setup but also in their respective environments.

Progranulin enhances the engraftment of transplanted human iPS cell-derived cerebral neurons.

Cerebral organoids (COs) in cell replacement therapy offer a viable approach to reconstructing neural circuits for individuals suffering from stroke or traumatic brain injuries. Successful transplantation relies on effective engraftment and neurite extension from the grafts. Earlier research has validated the effectiveness of delaying the transplantation procedure by 1 week. Here, we hypothesized that brain tissues 1 week following a traumatic brain injury possess a more favorable environment for cell transplantation when compared to immediately after injury. We performed a transcriptomic comparison to differentiate gene expression between these 2 temporal states. In controlled in vitro conditions, recombinant human progranulin (rhPGRN) bolstered the survival rate of dissociated neurons sourced from human induced pluripotent stem cell-derived COs (hiPSC-COs) under conditions of enhanced oxidative stress. This increase in viability was attributable to a reduction in apoptosis via Akt phosphorylation. In addition, rhPGRN pretreatment before in vivo transplantation experiments augmented the engraftment efficiency of hiPSC-COs considerably and facilitated neurite elongation along the host brain's corticospinal tracts. Subsequent histological assessments at 3 months post-transplantation revealed an elevated presence of graft-derived subcerebral projection neurons-crucial elements for reconstituting neural circuits-in the rhPGRN-treated group. These outcomes highlight the potential of PGRN as a neurotrophic factor suitable for incorporation into hiPSC-CO-based cell therapies.

Cerebral Microcirculation: Progress and Outlook of Laser Doppler Flowmetry in Neurosurgery and Neurointensive Care.

Laser Doppler flowmetry (LDF) is a well-established technique for the investigation of tissue microcirculation. Compared to skin, the use in the human brain is sparse. The measurement of cerebral microcirculation in neurointensive care and during neurosurgery is challenging and requires adaptation to the respective clinical setting. The aim of the review is to present state of the art and progress in neurosurgery and neurointensive care where LDF has proven useful and can find clinical importance in the investigation of cerebral microcirculation. The literature in the field is summarized and recent technical improvements regarding LDF systems and fiber optical probe designs for neurosurgical and neurocritical care described. By combining two signals from the LDF unit, the measurement of the microcirculation (Perfusion) and gray whiteness (TLI) of the brain tissue, the full potential of the device is achieved. For example, a forward-looking LDF-probe detects high-risk hemorrhage areas and gray-white matter boundaries along intraoperative trajectories during stereotactic neurosurgery. Proof of principles are given for LDF as a guidance tool in deep brain stimulation implantation, brain tumor needle biopsies, and as long-term monitoring device in neurocritical care. With well-designed fiber optical probes, surgical fixation, and signal processing for movement reduction, LDF monitoring of the cerebral microcirculation is successful up to 10 days. The use of LDF can be combined with other physiological measurement techniques, for example, fluorescence spectroscopy for identification of glioblastoma during tumor surgery. Fiber optics can also be used during magnetic resonance imaging (MRI). Despite the many advantages, fiber optical LDF has not yet reached its full potential in clinical neuro-applications. Multicenter studies are required to further evaluate LDF in neurosurgery and neurointensive care. In conclusion, the present status of LDF in neurosurgery and neurointensive care has been reviewed. By combining Perfusion and TLI with tailored probe designs the full potential of LDF can be achived in measuring cerebral microcirculation. This includes guidance during DBS implantation and needle biopsies, and long-term monitoring in neurocritical care.

Disruption of network hierarchy pattern in bulimia nervosa reveals brain information integration disorder

The human brain works as a hierarchical organization that is a continuous axis spanning sensorimotor cortex to transmodal cortex (referring to cortex that integrates multimodal sensory information and participates in complex cognitive functions). Previous studies have demonstrated abnormalities in several specific networks that may account for their multiple behavioral deficits in patients with bulimia nervosa (BN), but whether and how the network hierarchical organization changes in BN remain unknown. This study aimed to investigate alterations of the hierarchy organization in BN network and their clinical relevance. Connectome gradient analyses were applied to depict the network hierarchy patterns of fifty-nine patients with BN and thirty-nine healthy controls (HCs). Then, we evaluated the network- and voxel-level gradient alterations of BN by comparing gradient values in each network and each voxel between patients with BN and HCs. Finally, the association between altered gradient values and clinical variables was explored. In the principal gradient, patients with BN exhibited reduced gradient values in dorsal attention network and increased gradient values in subcortical regions compared to HCs. In the secondary gradient, patients with BN showed decreased gradient values in ventral attention network and increased gradient values in limbic network. Regionally, the areas with altered principal or secondary gradient values in BN group were mainly located in transmodal networks, i.e., the default-mode and frontoparietal network. In BN group, the principal gradient values of right inferior frontal gyrus were negatively associated with external eating behavior. This study revealed the disordered network hierarchy patterns in patients with BN, which suggested a disturbance of brain information integration from attention network and subcortical regions to transmodal networks in these patients. These findings may provide insight into the neurobiological underpinnings of BN.

The role of neuron-like cell lines and primary neuron cell models in unraveling the complexity of neurodegenerative diseases: a comprehensive review.

Neurodegenerative diseases (NDs) are characterized by the progressive loss of neurons. As to developing effective therapeutic interventions, it is crucial to understand the underlying mechanisms of NDs. Cellular models have become invaluable tools for studying the complex pathogenesis of NDs, offering insights into disease mechanisms, determining potential therapeutic targets, and aiding in drug discovery. This review provides a comprehensive overview of various cellular models used in ND research, focusing on Alzheimer's disease, Parkinson's disease, Huntington's disease, and amyotrophic lateral sclerosis. Cell lines, such as SH-SY5Y and PC12 cells, have emerged as valuable tools due to their ease of use, reproducibility, and scalability. Additionally, co-culture models, involving the growth of distinct cell types like neurons and astrocytes together, are highlighted for simulating brain interactions and microenvironment. While cell lines cannot fully replicate the complexity of the human brain, they provide a scalable method for examining important aspects of neurodegenerative diseases. Advancements in cell line technologies, including the incorporation of patient-specific genetic variants and improved co-culture models, hold promise for enhancing our understanding and expediting the development of effective treatments. Integrating multiple cellular models and advanced technologies offers the potential for significant progress in unraveling the intricacies of these debilitating diseases and improving patient outcomes.

Mechanically adaptive and deployable intracortical probes enable long-term neural electrophysiological recordings

Flexible intracortical probes offer important opportunities for stable neural interfaces by reducing chronic immune responses, but their advances usually come with challenges of difficult implantation and limited recording span. Here, we reported a mechanically adaptive and deployable intracortical probe, which features a foldable fishbone-like structural design with branching electrodes on a temperature-responsive shape memory polymer (SMP) substrate. Leveraging the temperature-triggered soft-rigid phase transition and shape memory characteristic of SMP, this probe design enables direct insertion into brain tissue with minimal footprint in a folded configuration while automatically softening to reduce mechanical mismatches with brain tissue and deploying electrodes to a broader recording span under physiological conditions. Experimental and numerical studies on the material softening and structural folding-deploying behaviors provide insights into the design, fabrication, and operation of the intracortical probes. The chronically implanted neural probe in the rat cortex demonstrates that the proposed neural probe can reliably detect and track individual units for months with stable impedance and signal amplitude during long-term implantation. The work provides a tool for stable neural activity recording and creates engineering opportunities in basic neuroscience and clinical applications.