Brain Regions Research Articles

Reciprocal crosslink among MeCP2/BDNF /CREB signaling pinpointed in autism spectrum disorder.

Autism spectrum disorder, or individual disability (ID), is a condition characterized by complications in social interaction, restricted repetitive behavior, and difficulties in social communication. Neuquinon (NQ) possess a powerful therapeutic potential in various neurodegenerative disease. Nevertheless, contributing to NQ's low water solubility and bioavailability, its medicinal use has been constrained. Liposomes were supposed to be prospective drug-delivering agents for NQ, crossing the blood-brain barrier (BBB), and reaching the target organs. The current investigation aims to track the signaling pathways that govern NQ and liposomal neuquinon (LNQ) action in autistic models generated by ethyl formic acid. The neurotransmitters gamma amino-butyric acid (GABA), acetylcholine (ACh), and acetylcholinesterase (AChE) in addition to, the gene expressions of brain-derived neurotrophic factor (BDNF), cAMP response element-binding protein (CREB), and methyl-CpG-binding protein 2 (MeCP2) and the DNA damage COMET analysis at different time intervals of the study, were assessed. EFA in a dose of 500mg/kg BW was used to induce autism in rats, and then NQ and LNQ were administered in 10mg/kg and 2mg/kg BW, respectively. The results revealed that NQ and LNQ significantly down-regulated BDNF, GABA, and AChE; on the other hand, they up-regulated MeCP2, CREB gene expressions, and ACh action. NQ and LNQ displayed improvement in DNA damage in almost all brain regions after EFA alterations; even better results were noticed post-LNQ therapy. Therefore, it may be concluded that neuquinon and liposomal-loaded neuquinon have a therapeutic index versus EFA-induced autism in a rat model.

Tau-PET in early cortical Alzheimer brain regions in relation to mild behavioral impairment in older adults with either normal cognition or mild cognitive impairment

Mild Behavioral Impairment (MBI) leverages later-life emergent and persistent neuropsychiatric symptoms (NPS) to identify a high-risk group for incident dementia. Phosphorylated tau (p-tau) is a hallmark biological manifestation of Alzheimer disease (AD). We investigated associations between MBI and tau accumulation in early-stage AD cortical regions. In 442 Alzheimer’s Disease Neuroimaging Initiative participants with normal cognition or mild cognitive impairment, MBI status was determined alongside corresponding p-tau and Aβ. Two meta-regions of interest were generated to represent Braak I and III neuropathological stages. Multivariable linear regression modelled the association between MBI as independent variable and tau tracer uptake as dependent variable. Among Aβ positive individuals, MBI was associated with tau uptake in Braak I (β=0.45(0.15), p<.01) and Braak III (β=0.24(0.07), p<.01) regions. In Aβ negative individuals, MBI was not associated with tau in the Braak I region (p=.11) with a negative association in Braak III (p=.01). These findings suggest MBI may be a sequela of neurodegeneration, and can be implemented as a cost-effective framework to help improve screening efficiency for AD.

Modeling realistic synaptic inputs of CA1 hippocampal pyramidal neurons and interneurons via Adaptive Generalized Leaky Integrate-and-Fire models

Computational models of brain regions are crucial for understanding neuronal network dynamics and the emergence of cognitive functions. However, current supercomputing limitations hinder the implementation of large networks with millions of morphological and biophysical accurate neurons. Consequently, research has focused on simplified spiking neuron models, ranging from the computationally fast Leaky Integrate and Fire (LIF) linear models to more sophisticated non-linear implementations like Adaptive Exponential (AdEX) and Izhikevic models, through Generalized Leaky Integrate and Fire (GLIF) approaches. However, in almost all cases, these models are tuned (and can be validated) only under constant current injections and they may not, in general, also reproduce experimental findings under variable currents. This study introduces an Adaptive GLIF (A-GLIF) approach that addresses this limitation by incorporating a new set of update rules. The extended A-GLIF model successfully reproduces both constant and variable current inputs, and it was validated against the results obtained using a biophysical accurate model neuron. This enhancement provides researchers with a tool to optimize spiking neuron models using classic experimental traces under constant current injections, reliably predicting responses to synaptic inputs, which can be confidently used for large-scale network implementations.

Neuroanatomical alterations in brain disorder: A magnetic resonance imaging analysis

Background: Bipolar disorder is a serious mental disorder caused by strong mood fluctuations, affecting 2% of the world's population. People with bipolar disorder experience both manic and depressive episodes, which can lead to suicidal thoughts and changes in appetite, activity, and focus. There are different subtypes of bipolar disorder, with cyclothymic disorder being the milder of the two. Bipolar I is characterized by manic periods, while bipolar II is marked by hypomanic and significant depressive episodes. Bipolar disorder is a biological, genetic, and environmental condition that can affect anyone at any age. Methods: In this study, we enrolled a total of 49 bipolar disorder (BD) participants to 44 healthy control (HC) subjects. Bipolar disorder patients were enlisted with their consent using web portals, medical facilities, and local marketing. MRI contraindications, medical history, self-reported using a mood-altering medication, inadequate vision, and left-handedness were among the exclusion criteria. The various tissue structures which are: the gray matter (GM), white matter (WM), and cerebrospinal fluid (CSF) were examined using voxel-based morphometry (VBM) to ascertain these changes. We employed statistical parametric mapping (SPM) for both image processing and statistical analysis. Results: Our findings demonstrate that individuals with bipolar disorder showed a substantial volume decrease in both gray matter (GM) and white matter (WM), with gray matter (GM) and white matter (WM) volume decreases being more noticeable in the frontal, temporal, parietal, and occipital lobes. Additionally, individuals with bipolar disorder showed no CSF volume in any of the brain regions. Conclusion: Our VBM research backs up earlier studies that link changes in brain structure, particularly gray matter and white matter, to bipolar disorder. These discoveries shed more information on the neurology of bipolar disorder and could guide the creation of more potent diagnostic and treatment modalities.

Characterization of posterior circulation blood perfusion in patients with different degrees of basilar artery tortuosity.

The morphology of basilar artery (BA) may affect posterior circulation blood perfusion. We aimed to investigate whether different degrees of BA tortuosity could lead to the alterations of posterior circulation perfusion. We collected 138 subjects with different BA tortuosity scores, including 32 cases of score 0, 45 cases of score 1, 43 cases of score 2, and 18 cases of score 3. A higher score represented a higher degree of BA tortuosity. Ordered logistic regression analysis was performed to investigate the risk factors for BA tortuosity. We quantitatively measured the cerebral blood flow (CBF) in eight posterior circulation brain regions using arterial spin labeling. SPSS 25.0 was used for statistical analysis. The correlation between the CBF and BA tortuosity was corrected by the Bonferroni method. The significance level was set at 0.006 (0.05/8). Hypertension (HR: 2.39; 95%CI: 1.23-4.71; P = 0.01) and vertebral artery dominance (HR: 2.38; 95%CI: 1.10-4.67; P = 0.03) were risk factors for BA tortuosity. CBF in occipital gray matter (R = -0.383, P < 0.001), occipital white matter (R = -0.377, P < 0.001), temporal gray matter (R = -0.292, P = 0.001), temporal white matter (R = -0.297, P < 0.001), and cerebellum (R = -0.328, P < 0.001) were negatively correlated with BA tortuosity degree. No significant correlation was found between the BA tortuosity degree and CBF in hippocampus (R = -0.208, P = 0.014), thalamus (R = -0.001, P = 0.988) and brainstem (R = -0.204, P = 0.016). BA tortuosity could affect posterior circulation blood perfusion. CBF was negatively correlated with BA tortuosity degree. The morphology of BA may serve as a biomarker for posterior circulation and the severity of posterior circulation ischemia.

Neural correlates of obesity across the lifespan

Associations between brain and obesity are bidirectional: changes in brain structure and function underpin over-eating, while chronic adiposity leads to brain atrophy. Investigating brain-obesity interactions across the lifespan can help better understand these relationships. This study explores the interaction between obesity and cortical morphometry in children, young adults, adults, and older adults. We also investigate the genetic, neurochemical, and cognitive correlates of the brain-obesity associations. Our findings reveal a pattern of lower cortical thickness in fronto-temporal brain regions associated with obesity across all age cohorts and varying age-dependent patterns in the remaining brain regions. In adults and older adults, obesity correlates with neurochemical changes and expression of inflammatory and mitochondrial genes. In children and older adults, adiposity is associated with modifications in brain regions involved in emotional and attentional processes. Thus, obesity might originate from cognitive changes during early adolescence, leading to neurodegeneration in later life through mitochondrial and inflammatory mechanisms.

Non-motor symptoms in patients with amyotrophic lateral sclerosis: current state and future directions.

Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease characterized by the progressive degeneration of both upper and lower motor neurons. A defining histopathological feature in approximately 97% of all ALS cases is the accumulation of phosphorylated trans-activation response (TAR) DNA-binding protein 43 protein (pTDP-43) aggregates in the cytoplasm of neurons and glial cells within the central nervous system. Traditionally, it was believed that the accumulation of TDP-43 aggregates and subsequent neurodegeneration primarily occurs in motor neurons. However, contemporary evidence suggests that as the disease progresses, other systems and brain regions are also affected. Despite this, there has been a limited number of clinical studies assessing the non-motor symptoms in ALS patients. These studies often employ various outcome measures, resulting in a wide range of reported frequencies of non-motor symptoms in ALS patients. The importance of assessing the non-motor symptoms reflects in a fact that they have a significant impact on patients' quality of life, yet they frequently go underdiagnosed and unreported during clinical evaluations. This review aims to provide an up-to-date overview of the current knowledge concerning non-motor symptoms in ALS. Furthermore, we address their diagnosis and treatment in everyday clinical practice.

Long non-coding RNAs expression and regulation across different brain regions in primates

Human and non-human primates have strikingly similar genomes, but they strongly differ in many brain-based processes (e.g., behaviour and cognition). While the functions of protein-coding genes have been extensively studied, rather little is known about the role of non-coding RNAs such as long non-coding RNAs (lncRNAs). Here, we predicted lncRNAs and analysed their expression pattern across different brain regions of human and non-human primates (chimpanzee, gorilla, and gibbon). Our analysis identified shared orthologous and non-orthologous lncRNAs, showing striking differences in the genomic features. Differential expression analysis of the shared orthologous lncRNAs from humans and chimpanzees revealed distinct expression patterns in subcortical regions (striatum, hippocampus) and neocortical areas while retaining a homogeneous expression in the cerebellum. Co-expression analysis of lncRNAs and protein-coding genes revealed massive proportions of co-expressed pairs in neocortical regions of humans compared to chimpanzees. Network analysis of co-expressed pairs revealed the distinctive role of the hub-acting orthologous lncRNAs in a region- and species-specific manner. Overall, our study provides novel insight into lncRNA driven gene regulatory landscape, neural regulation, brain evolution, and constitutes a resource for primate’s brain lncRNAs.

The characteristics of brain atrophy prior to the onset of Alzheimer’s disease: a longitudinal study

ObjectiveWe aimed to use the onset time of Alzheimer’s disease (AD) as the reference time to longitudinally investigate the atrophic characteristics of brain structures prior to the onset of AD.Materials and methodsA total of 328 participants from the ADNI database with clear onset of AD and structural imaging data were included in our study. The time before the onset of AD (abbreviated as BAD) was calculated. We investigated the longitudinal brain changes in 97 regions using multivariate linear mixed effects regression models.ResultsThe average BAD was −28.15 months, with a range from −156 to 0 months. The 54 brain regions showed significant atrophy prior to the onset of AD, and these regions were mainly distributed in the frontal and temporal lobes. The parietal and occipital lobe exhibited relatively less atrophy than the other brain lobes. Sex, age, and magnetic field strength had greater direct impacts on structural indicators than APOE genotype and education. The analysis of interaction effects revealed that the APOE ε4 mutation carriers exhibited more severe structural changes in specific brain regions as the BAD increased. However, sex, age, and education had minimal regulatory influence on the structural changes associated with BAD.ConclusionLongitudinal analysis, with the onset time point of AD as the reference, can accurately describe the features of structural changes preceding the onset of AD and provide a comprehensive understanding of AD development.

Expression of Dystrophin Dp71 Splice Variants Is Temporally Regulated During Rodent Brain Development.

Dystrophin Dp71 is the major product of the Duchenne muscular dystrophy (DMD) gene in the brain, and its loss in DMD patients and mouse models leads to cognitive impairments. Dp71 is expressed as a range of proteins generated by alternative splicing of exons 71 to 74 and 78, classified in the main Dp71d and Dp71f groups that contain specific C-terminal ends. However, it is unknown whether each isoform has a specific role in distinct cell types, brain regions, and/or stages of brain development. In the present study, we characterized the expression of Dp71 isoforms during fetal (E10.5, E15.5) and postnatal (P1, P7, P14, P21 and P60) mouse and rat brain development. We finely quantified the expression of several Dp71 transcripts by RT-PCR and cloning assays in samples from whole-brain and distinct brain structures. The following Dp71 transcripts were detected: Dp71d, Dp71d∆71, Dp71d∆74, Dp71d∆71,74, Dp71d∆71-74, Dp71f, Dp71f∆71, Dp71f∆74, Dp71f∆71,74, and Dp71fΔ71-74. We found that the Dp71f isoform is the main transcript expressed at E10.5 (> 80%), while its expression is then progressively reduced and replaced by the expression of isoforms of the Dp71d group from E15.5 to postnatal and adult ages. This major finding was confirmed by third-generation nanopore sequencing. In addition, we found that the level of expression of specific Dp71 isoforms varies as a function of postnatal stages and brain structure. Our results suggest that Dp71 isoforms have different and complementary roles during embryonic and postnatal brain development, likely taking part in a variety of maturation processes in distinct cell types.

Association of synaptic density and cognitive performance in temporal lobe epilepsy: Humans and animals PET imaging study with [18F]SynVesT-1.

Cognitive impairment is a common comorbidity in individuals with temporal lobe epilepsy (TLE), yet the underlying mechanisms remain unknown. This study explored the putative association between in vivo synaptic loss and cognitive outcomes in TLE patients by PET imaging of synaptic vesicle glycoprotein 2A (SV2A). We enrolled 16 TLE patients and 10 cognitively normal controls. All participants underwent SV2A PET imaging using [18F]SynVesT-1 and cognitive assessment. Lithium chloride-pilocarpine-induced rats with status epilepticus (n = 20) and controls (n = 6) rats received levetiracetam (LEV, specifically binds to SV2A), valproic acid (VPA), or saline for 14 days. Then, synaptic density was quantified by [18F]SynVesT-1 micro-PET/CT. The novel object recognition and Morris water maze tests evaluated TLE-related cognitive function. SV2A expression was examined and confirmed by immunohistochemistry. Temporal lobe epilepsy patients showed significantly reduced synaptic density in hippocampus, which was associated with cognitive performance. In the rat model of TLE, the expression of SV2A and synaptic density decreased consistently in a wider range of brain regions, including the entorhinal cortex, insula, hippocampus, amygdala, thalamus, and cortex. We treated TLE animal models with LEV or VPA to explore whether synaptic loss contributes to cognitive deficits. It was found that LEV significantly exerted protective effects against brain synaptic deficits and cognitive impairment. This is the first study to link synaptic loss to cognitive deficits in TLE, suggesting [18F]SynVesT-1 PET could be a promising biomarker for monitoring synaptic loss and cognitive dysfunction. LEV might help reverse synaptic deficits and ameliorate learning and memory impairments in TLE patients.

Inflammatory and immunopathological differences in brains of permissive and non-permissive hosts with Angiostrongylus cantonensis infection can be identified using 18F/FDG/PET-imaging.

Angiostrongylus cantonensis is a parasite that mainly infects the heart and pulmonary arteries of rats and causes human eosinophilic meningitis or meningoencephalitis in certain geographical areas. Current diagnostic methods include detection of the parasite in cerebrospinal fluid (CSF) and eosinophilic immune examination after lumbar puncture, which may be risky and produce false-positive results. 18F- Fluorodeoxyglucose (FDG), a Positron emission tomography (PET) tracer, has been used to assess different pathological or inflammatory changes in the brains of patients. In this study, we hypothesized that A. cantonensis infection-induced inflammatory and immunomodulatory factors of eosinophils result in localized pathological changes in the brains of non-permissive hosts, which could be analyzed using in vivo 18F-FDG PET imaging. Non-permissive host ICR mice and permissive host SD rats were infected with A. cantonensis, and the effects of the resulting inflammation on 18F-FDG uptake were characterized using PET imaging. We also quantitatively measured the distributed uptake values of different brain regions to build an evaluated imaging model of localized neuropathological damage caused by eosinophilic inflammation. Our results showed that the uptake of 18F-FDG increased in the cerebellum, brainstem, and limbic system of mice at three weeks post-infection, whereas the uptake in the rat brain was not significant. Immunohistochemical staining and western blotting revealed that Iba-1, a microglia-specific marker, significantly increased in the hippocampus and its surrounding area in mice after three weeks of infection, and then became pronounced after four weeks of infection; while YM-1, an eosinophilic chemotactic factor, in the hippocampus and midbrain, increased significantly from two weeks post-infection, sharply escalated after three weeks of infection, and peaked after four weeks of infection. Cytometric bead array (CBA) analysis revealed that the expression of TNF in the serum of mice increased concomitantly with the prolongation of infection duration. Furthermore, IFN-γ and IL-4 in rat serum were significantly higher than in mouse serum at two weeks post-infection, indicating significantly different immune responses in the brains of rats and mice. We suggest that 18F-FDG uptake in the host brain may be attributed to the accumulation of large numbers of immune cells, especially the metabolic burst of activated eosinophils, which are attracted to and induced by activated microglia in the brain. An in vivo 18F-FDG/PET imaging model can be used to evaluate live neuroinflammatory pathological changes in the brains of A. cantonensis-infected mice and rats.

Brain wide representation of social knowledge.

Understanding how the human brain maps different dimensions of social conceptualizations remains a key unresolved issue. We performed a functional MRI study in which participants were exposed to audio definitions of personality traits and asked to simulate experiences associated with the concepts. Half of the concepts were affective (e.g. empathetic) and the other half were non-affective (e.g. intelligent). Orthogonally, half of the concepts were highly likable (e.g. sincere) and half were socially undesirable (e.g. liar). Behaviourally, we observed that the dimension of social desirability reflected the participant's subjective ratings better than affect. FMRI decoding results showed that both social desirability and affect could be decoded in local patterns of activity through distributed brain regions including the superior temporal, inferior frontal, precuneus and key nodes of the default mode network in posterior/anterior cingulate and ventromedial prefrontal cortex. Decoding accuracy was better for social desirability than affect. A representational similarity analysis further demonstrated that a deep language model significantly predicted brain activity associated with the concepts in bilateral regions of superior and anterior temporal lobe. The results demonstrate a brain wide representation of social knowledge, involving default model network systems that support the multimodal simulation of social experience, with a further reliance on language related preprocessing.

Evaluation of Rural Healing Landscape DESIGN Based on Virtual Reality and Electroencephalography

From the user’s perspective, emotional elements are increasingly being used in design. Researchers have indicated that healing landscapes in rural areas play a positive role in soothing human emotions. In this study, a landscape with healing functions was designed, and 32 subjects experienced emotions in a virtual reality (VR) scene while their 32-channel electroencephalography (EEG) signals were collected. This study compared the brain responses with and without the presence of healing landscape elements and conducted correlation coefficient analysis using eight different regression prediction models to examine the relationship between security, comfort, positivity, and corresponding healing landscape elements. The results show significant improvements in emotions of security, comfort, and positivity post-exposure to the landscape design, especially with certain elements, such as seating, shrubs, and tree pools. EEG data indicate enhanced emotional and cognitive states, particularly relaxation, with increased activity in specific brain regions. The decision tree regression model is the most suitable for our data. It reveals strong correlations between specific healing landscape elements and emotional responses. In the comfort category, “shrubs” show the highest correlation (R² = 0.82), while in the security category, “trees” have the highest correlation (R² = 0.77). Similarly, in the positivity category, “trees” again exhibit the highest correlation (R² = 0.71) with EEG data, indicating their significant impact on these emotional dimensions. This study demonstrates the importance of using scientific methods, such as EEG technology, to validate the principles of emotional design and also underscores the role of green environments in enhancing psychological health and emotional comfort.

Altered morphometric similarity networks in insomnia disorder.

Previous studies on structural covariance network (SCN) suggested that patients with insomnia disorder (ID) show abnormal structural connectivity, primarily affecting the somatomotor network (SMN) and default mode network (DMN). However, evaluating a single structural index in SCN can only reveal direct covariance relationship between two brain regions, failing to uncover synergistic changes in multiple structural features. To cover this research gap, the present study utilized novel morphometric similarity networks (MSN) to examine the morphometric similarity between cortical areas in terms of multiple sMRI parameters measured at each area. With seven T1-weighted imaging morphometric features from the Desikan-Killiany atlas, individual MSN was constructed for patients with ID (N = 87) and healthy control groups (HCs, N = 84). Two-sample t-test revealed differences in MSN between patients with ID and HCs. Correlation analyses examined associations between MSNs and sleep quality, insomnia symptom severity, and depressive symptoms severity in patients with ID. The right paracentral lobule (PCL) exhibited decreased morphometric similarity in patients with ID compared to HCs, mainly manifested by its de-differentiation (meaning loss of distinctiveness) with the SMN, DMN, and ventral attention network (VAN), as well as its decoupling with the visual network (VN). Greater PCL-based de-differentiation correlated with less severe insomnia and fewer depressive symptoms in the patients group. Additionally, patients with less depressive symptoms showed greater PCL de-differentiation from the SMN. As an important pilot step in revealing the underlying morphometric similarity alterations in insomnia disorder, the present study identified the right PCL as a hub region that is de-differentiated with other high-order networks. Our study also revealed that MSN has an important potential to capture clinical significance related to insomnia disorder.

EEG Emotion Recognition Network Based on Attention and Spatiotemporal Convolution

Human emotions are complex psychological and physiological responses to external stimuli. Correctly identifying and providing feedback on emotions is an important goal in human–computer interaction research. Compared to facial expressions, speech, or other physiological signals, using electroencephalogram (EEG) signals for the task of emotion recognition has advantages in terms of authenticity, objectivity, and high reliability; thus, it is attracting increasing attention from researchers. However, the current methods have significant room for improvement in terms of the combination of information exchange between different brain regions and time–frequency feature extraction. Therefore, this paper proposes an EEG emotion recognition network, namely, self-organized graph pesudo-3D convolution (SOGPCN), based on attention and spatiotemporal convolution. Unlike previous methods that directly construct graph structures for brain channels, the proposed SOGPCN method considers that the spatial relationships between electrodes in each frequency band differ. First, a self-organizing map is constructed for each channel in each frequency band to obtain the 10 most relevant channels to the current channel, and graph convolution is employed to capture the spatial relationships between all channels in the self-organizing map constructed for each channel in each frequency band. Then, pseudo-three-dimensional convolution combined with partial dot product attention is implemented to extract the temporal features of the EEG sequence. Finally, LSTM is employed to learn the contextual information between adjacent time-series data. Subject-dependent and subject-independent experiments are conducted on the SEED dataset to evaluate the performance of the proposed SOGPCN method, which achieves recognition accuracies of 95.26% and 94.22%, respectively, indicating that the proposed method outperforms several baseline methods.

Localization of stuttering based on causal brain lesions.

Stuttering affects approximately 1 in 100 adults and can result in significant communication problems and social anxiety. It most often occurs as a developmental disorder but can also be caused by focal brain damage. These latter cases may lend unique insight into the brain regions causing stuttering. Here, we investigated the neuroanatomical substrate of stuttering using three independent datasets: (i) case reports from the published literature of acquired neurogenic stuttering following stroke (n = 20, 14 males/six females, 16-77 years); (ii) a clinical single study cohort with acquired neurogenic stuttering following stroke (n = 20, 13 males/seven females, 45-87 years); and (iii) adults with persistent developmental stuttering (n = 20, 14 males/six females, 18-43 years). We used the first two datasets and lesion network mapping to test whether lesions causing acquired stuttering map to a common brain network. We then used the third dataset to test whether this lesion-based network was relevant to developmental stuttering. In our literature dataset, we found that lesions causing stuttering occurred in multiple heterogeneous brain regions, but these lesion locations were all functionally connected to a common network centred around the left putamen, including the claustrum, amygdalostriatal transition area and other adjacent areas. This finding was shown to be specific for stuttering (PFWE < 0.05) and reproducible in our independent clinical cohort of patients with stroke-induced stuttering (PFWE < 0.05), resulting in a common acquired stuttering network across both stroke datasets. Within the common acquired stuttering network, we found a significant association between grey matter volume and stuttering impact for adults with persistent developmental stuttering in the left posteroventral putamen, extending into the adjacent claustrum and amygdalostriatal transition area (PFWE < 0.05). We conclude that lesions causing acquired neurogenic stuttering map to a common brain network, centred to the left putamen, claustrum and amygdalostriatal transition area. The association of this lesion-based network with symptom severity in developmental stuttering suggests a shared neuroanatomy across aetiologies.

Intellectual Deepening Influences the Development and Expression of Introversion

This scholarly investigation delves into the neurological interplay between enhanced intellectual engagement and social interaction preferences, focusing on the critical role of specific brain regions and neurotransmitter modulation. Activation patterns in the hippocampus and the prefrontal cortex, particularly influenced by neurotransmitters such as dopamine and serotonin, are explored in relation to their impact on memory enhancement and social motivation. Elevated activity in these brain areas can enhance retention of intellectually stimulating stimuli, potentially fostering social isolation. This research elucidates the neurochemical variations that influence social engagement capacities and clarifies the underlying biological mechanisms predisposing highly intellectual individuals to favor isolation over less stimulating social interactions. This study aims to deepen the understanding of how neuroanatomical and neurochemical dynamics shape introverted behaviors and preference for solitary activities, thereby influencing social integration processes.

Research progress of acupuncture regulating ERK signaling pathway in the treatment of depression.

Acupuncture treatment for depression has definite therapeutic efficacy, and its mechanism has been extensively studied. The extracellular regulatory protein kinase(ERK) signaling pathway is involved in the development and progression of depression. This article reviewed and summarized the research progress on the regulation of the ERK signaling pathway by acupuncture in the treatment of depression in recent years, focusing on the physiological activation and regulatory mechanism of the ERK signaling pathway, its association with the occurrence of depression, and the mechanisms through which acupuncture activates the ERK signaling pathway to treat depression (including enhancing neuronal synaptic plasticity, promoting the release of neurotrophic factors, and inhibiting neuronal apoptosis). Future research could explore the relationship between the ERK pathway and other pathways, investigate other brain regions besides the prefrontal cortex and hippocampus, examine differences in regulatory mechanisms between male and female patients, assess the effects of different acupuncture techniques on the ERK pathway, and increase efforts to explore mechanism of synaptic plasticity regulation, so as to provide reference for the clinical application and mechanism sludy of acupuncture in depression treatment.

Lipidome atlas of the adult human brain

Lipids are the most abundant but poorly explored components of the human brain. Here, we present a lipidome map of the human brain comprising 75 regions, including 52 neocortical ones. The lipidome composition varies greatly among the brain regions, affecting 93% of the 419 analyzed lipids. These differences reflect the brain’s structural characteristics, such as myelin content (345 lipids) and cell type composition (353 lipids), but also functional traits: functional connectivity (76 lipids) and information processing hierarchy (60 lipids). Combining lipid composition and mRNA expression data further enhances functional connectivity association. Biochemically, lipids linked with structural and functional brain features display distinct lipid class distribution, unsaturation extent, and prevalence of omega-3 and omega-6 fatty acid residues. We verified our conclusions by parallel analysis of three adult macaque brains, targeted analysis of 216 lipids, mass spectrometry imaging, and lipidome assessment of sorted murine neurons.