Cortical Regions Research Articles

GC/MS and LC-ESI-MS Analysis of Conocarpus erectus Leaves Extract via Regulating Amyloid-β-Peptide, Tau Protein, Neurotransmitters, Inflammation and Oxidative Stress against AlCl3-Induced Alzheimer's Disease in Rats.

This study investigated the therapeutic effect of Conocarpus erectus leaves methanolic extract against AlCl3 -induced Alzheimer's disease (AD) in rats comparing with Donepezil-hydrochloride as a reference drug. The bioactive compounds of C. erectus leaves were isolated and identified by GC/MS and LC-ESI-MS analysis. Malondialdehyde (MDA), reduced glutathione (GSH), superoxide dismutase (SOD), tumor necrosis factor-alpha (TNF-α), interleukin-6 (IL-6), amyloid-β-peptide (Aβ-peptide), tau protein, acetylcholinesterase (AChE), serotonin (5-HT), dopamine (DA) and nor-adrenaline (NE) levels were estimated. The neuromuscular strength, memory behavior and histopathological examination of cerebral cortex region were also conducted. Forty-three compounds were characterized from the non-polar fraction of C. erectus L. leaves extract and nineteen compounds were identified from the defatted extract. AlCl3- induction caused significant elevation of brain oxidative stress, Aβ-peptide, tau protein, IL-6, TNF-α and AChE levels. A significant decrease in 5-HT, ND and DA levels were noticed. Additionally, AlCl3 reduced neuromuscular strength and compromised memory function. Treatment of AlCl3- induced rats with C. erectuse extract ameliorated these selected parameters by variable degrees. In conclusion, C. erectus protects against AlCl3- induced AD in rats through its antioxidant, anti-inflammatory, and antineutron damage. It could be considered as a new nutraceutical agent for attenuating symptoms associated with Alzheimer's disease.

Outer Retinal Thinning is Associated With Brain Atrophy in Early Age-Related Macular Degeneration

Both retinal changes and age-related macular degeneration (AMD) have been shown to be associated with Alzheimer's disease and related dementias (ADRD). In AMD, the outer retina is impacted significantly and early, but little is known about its association with cognition or changes in brain morphometry. This study investigates the relationship between retinal and brain morphometry in older adults with early and intermediate AMD. Cross-sectional study. Adults ≥70 years with normal, early, and intermediate AMD were recruited from Callahan Eye Hospital Clinics at the University of Alabama at Birmingham. Participants underwent cognitive testing, optical coherence tomography, and magnetic resonance imaging. Associations of retinal layer thickness with brain volume and thickness of specific brain regions were evaluated utilizing multivariable linear regression. The relevance of retinal thickness variables in brain volumetrics was quantified using least absolute shrinkage and selection operator regression models. Correlations between demographic variables, cognitive scores, and brain morphometry were evaluated. Participants with thinner outer retina had significantly smaller hippocampus (β = 0.019, P = .022), lower occipital cortex regions of interest (occipital ROIs) thickness (β = 5.68, P = .020), and lower cortical thickness in ADRD-related brain regions (β = 7.72, P = .006). People with thinner total retina had significantly lower occipital ROIs (β = 3.19, P = .009) and ADRD-related brain region (β = 3.94, P = .005) thickness. Outer retinal thickness in the outer Early Treatment of Diabetic Retinopathy Study ring was the most frequently reported retinal variable associated with brain morphometry on least absolute shrinkage and selection operator regression. Total gray matter volume showed positive correlations with education (Pearson's r = 0.30, P = .022). In older adults with normal retinal aging and early and intermediate AMD, thinner outer retina had specific associations with brain regions primarily involved in vision and cognition, such as lower hippocampal volume and lower thickness of the occipital ROIs and brain regions known to show early structural changes in dementia.

11C-UCB-J PET imaging is consistent with lower synaptic density in autistic adults.

The neural bases of autism are poorly understood at the molecular level, but evidence from animal models, genetics, post-mortem studies, and single-gene disorders implicate synaptopathology. Here, we use positron emission tomography (PET) to assess the density of synapses with synaptic vesicle glycoprotein 2A (SV2A) in autistic adults using 11C-UCB-J. Twelve autistic (mean (SD)age 25 (4)years; six males), and twenty demographically matched non-autistic individuals (26 (3)years; eleven males) participated in a 11C-UCB-J PET scan. Binding potential, BPND, was the primary outcome measure and computed with the centrum semiovale as the reference region. Partial volume correction with Iterative Yang was applied to control for possible volumetric differences. Mixed-model statistics were calculated for between-group differences. Relationships to clinical characteristics were evaluated based on clinician ratings of autistic features. Whole cortex synaptic density was 17% lower in the autism group (p = 0.01). All brain regions in autism had lower 11C-UCB-J BPND compared to non-autistic participants. This effect was evident in all brain regions implicated in autism. Significant differences were observed across multiple individual regions, including the prefrontal cortex (-15%, p = 0.02), with differences most pronounced in gray matter (p < 0.0001). Synaptic density was significantly associated with clinical measures across the whole cortex (r = 0.67, p = 0.02) and multiple regions (rs = -0.58 to -0.82, ps = 0.05 to <0.01). The first in vivo investigation of synaptic density in autism with PET reveals pervasive and large-scale lower density in the cortex and across multiple brain areas. Synaptic density also correlated with clinical features, such that a greater number of autistic features were associated with lower synaptic density. These results indicate that brain-wide synaptic density may represent an as-yet-undiscovered molecular basis for the clinical phenotype of autism and associated pervasive alterations across a diversity of neural processes.

Brain Iron in signature regions relating to cognitive aging in older adults: the Taizhou Imaging Study

BackgroundRecent magnetic resonance imaging (MRI) studies have established that brain iron accumulation might accelerate cognitive decline in Alzheimer’s disease (AD) patients. Both normal aging and AD are associated with cerebral atrophy in specific regions. However, no studies have investigated aging- and AD-selective iron deposition-related cognitive changes during normal aging. Here, we applied quantitative susceptibility mapping (QSM) to detect iron levels in cortical signature regions and assessed the relationships among iron, atrophy, and cognitive changes in older adults.MethodsIn this Taizhou Imaging Study, 770 older adults (mean age 62.0 ± 4.93 years, 57.5% women) underwent brain MRI to measure brain iron and atrophy, of whom 219 underwent neuropsychological tests nearly every 12 months for up to a mean follow-up of 2.68 years. Global cognition was assessed using the Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA). Domain-specific cognitive scores were obtained from MoCA subscore components. Regional analyses were performed for cortical regions and 2 signature regions where atrophy affected by aging and AD only: Aging (AG) -specific and AD signature meta-ROIs. The QSM and cortical morphometry means of the above ROIs were also computed.ResultsSignificant associations were found between QSM levels and cognitive scores. In particular, after adjusting for cortical thickness of regions of interest (ROIs), participants in the upper tertile of the cortical and AG-specific signature QSM exhibited worse ZMMSE than did those in the lower tertile [β\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\:\\beta\\:$$\\end{document} = -0.104, p = 0.026; β\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\:\\beta\\:$$\\end{document} = -0.118, p = 0.021, respectively]. Longitudinal analysis suggested that QSM values in all ROIs might predict decline in ZMoCA and key domains such as attention and visuospatial function (all p < 0.05). Furthermore, iron levels were negatively correlated with classic MRI markers of cortical atrophy (cortical thickness, gray matter volume, and local gyrification index) in total, AG-specific signature and AD signature regions (all p < 0.05).ConclusionAG- and AD-selective iron deposition was associated with atrophy and cognitive decline in elderly people, highlighting its potential as a neuroimaging marker for cognitive aging.

Chronobiological Spatial Clusters of Cortical Regions in the Human Brain.

We demonstrate that different regions of the cerebral cortex have different diurnal rhythms of spontaneously occurring high-frequency oscillations (HFOs). High-frequency oscillations were assessed with standard-of-care stereotactic electroencephalography in patients with drug-resistant epilepsy. To ensure generalizability of our findings beyond patients with drug-resistant epilepsy, we excluded stereotactic electroencephalography electrode contacts lying within seizure-onset zones, epileptogenic lesions, having frequent epileptiform activity, and excessive artifact. For each patient, we evaluated twenty-four 5-minute stereotactic electroencephalography epochs, sampled hourly throughout the day, and obtained the HFO rate (number of HFOs/minute) in every stereotactic electroencephalography channel. We analyzed diurnal rhythms of the HFO rates with the cosinor model and clustered neuroanatomic parcels in a standard brain space based on similarity of their cosinor parameters. Finally, we compared overlap among resting-state networks, described in the neuroimaging literature, and chronobiological spatial clusters discovered by us. We found five clusters that localized predominantly or exclusively to the left perisylvian, left perirolandic and left temporal, right perisylvian and right parietal, right frontal, and right insular-opercular cortices, respectively. These clusters were characterized by similarity of the HFO rates according to the time of the day. Also, these chronobiological spatial clusters preferentially overlapped with specific resting-state networks, particularly default mode network (clusters 1 and 3), frontoparietal network (cluster 1), visual network (cluster 1), and mesial temporal network (cluster 2). This is probably the first human study to report clusters of cortical regions with similar diurnal rhythms of electrographic activity. Overlap with resting-state networks attests to their functional significance and has implications for understanding cognitive functions and epilepsy-related mortality.

Detection of Alzheimer's Disease Using Hybrid Meta-ROI of MRI Structural Images.

The averaged cortical thickness of meta-ROI is currently being used for the diagnosis and prognosis of Alzheimer's disease (AD) using structural MRI brain images. The purpose of this work is to present a hybrid meta-ROI for the detection of AD. The AD detectability of selected cortical and volumetric regions of the brain was examined using signal detection theory. The top performing cortical and volumetric ROIs were taken as input nodes to the artificial neural network (ANN) for AD classification. An AD diagnostic accuracy of 91.9% was achieved by using a hybrid meta-ROI consisting of thicknesses of entorhinal and middle temporal cortices, and the volumes of the hippocampus and inferior lateral ventricles. Pairing inferior lateral ventricle dilation with hippocampal volume reduction improves AD detectability by 5.1%. Hybrid meta-ROI, including the dilation of inferior lateral ventricles, outperformed both cortical thickness- and volumetric-based meta-ROIs in the detection of Alzheimer's disease.

Examining relationships among NODDI indices of white matter structure in prefrontal cortical-thalamic-striatal circuitry and OCD symptomatology

Obsessive-compulsive disorder is a psychiatric disorder characterized by intrusive thoughts and repetitive behaviors. There are two prominent features: Harm Avoidance (HA) and Incompleteness (INC). Previous resting-state studies reported abnormally elevated connectivity between prefrontal cortical (PFC) and subcortical regions (thalamus, striatum) in OCD participants. Yet, little is known about the white matter (WM) structural abnormalities in these connections. Using brain parcellation and segmentation, whole brain tractography, and Neurite Orientation Dispersion and Density Imaging (NODDI), we aimed to characterize WM structural abnormalities in OCD vs. healthy controls and determine the extent to which NODDI indices of these connections were associated with subthreshold-threshold HA, INC and overall OCD symptom severity across all participants. Four PFC regions were segmented: ventral medial (vmPFC), ventrolateral (vlPFC), dorsomedial (dmPFC), and dorsolateral (dlPFC). NODDI Neurite Density (NDI) and Orientation Dispersion (ODI) indices of WM structure were extracted from connections between these PFC regions and the thalamus (42 OCD, 44 healthy controls, mean age[SD] = 23.65[4.25]y, 63.9% female) and striatum (38 OCD, 41 healthy controls, mean age[SD] = 23.59[4.27]y, 64.5% female). Multivariate analyses of covariance revealed no between-group differences in these indices. Multivariate regression models revealed that greater NDI in vmPFC-thalamus, greater NDI and ODI in vmPFC-striatum, and greater NDI in dmPFC-thalamus connections were associated with greater INC severity (Q ≤ 0.032). These findings highlight the utility of NODDI in the examination of WM structure in OCD, provide valuable insights into specific WM alterations underlying dimensional INC, and can facilitate the development of customized treatments for OCD individuals with treatment-resistant symptoms.

Thalamus and its functional connections with cortical regions contribute to complexity-dependent cognitive reasoning

The thalamus is crucial for supporting various cognitive behaviors due to its extensive connectivity with multiple cortical regions. However, the role of the thalamus and its functional connections with cortical regions in cognitive reasoning remains unclear, since previous research has mainly focused on cortical regions when studying the neural mechanisms underlying cognitive reasoning. To fill this knowledge gap, we utilized 7 T functional magnetic resonance imaging (fMRI) to study the activation patterns of the thalamus and its functional connections with cortical regions during cognitive reasoning task, while also examining how the complexity of reasoning tasks affects thalamic activation and functional connections with cortical regions. Our findings showed that cognitive reasoning processes are related to increased activation of the thalamus and its functional connections with a specific set of cortical regions, consisting of dorsolateral prefrontal cortex, inferior frontal sulcus, intraparietal sulcus, anterior cingulate cortex/presupplementary motor area, precuneus, and ventral medial prefrontal cortex. Moreover, the increase in relational complexity of the reasoning tasks led to a corresponding increase in thalamic activation and functional connectivity with cortical regions. Given the complex thalamus structure, including multiple distinct nuclei exhibiting specific functional connections with particular cortical regions, we used an atlas defined thalamic subdivisions based on its structural connectivity with different cortical regions. Our findings indicated that these different thalamic subregions not only exhibited distinct connectivity patterns with specific cortical regions during performance of cognitive reasoning, but also showed distinct connectivity patterns varied with task complexity. Overall, our study presents evidence of the thalamus’s role and its connections with cortical regions in supporting increasingly complex cognitive reasoning behavior, illuminating its contribution to higher-order cognitive functions, such as reasoning.

An Audio-Visual Speech Separation Model Inspired by Cortico-Thalamo-Cortical Circuits.

Audio-visual approaches involving visual inputs have laid the foundation for recent progress in speech separation. However, the optimization of the concurrent usage of auditory and visual inputs is still an active research area. Inspired by the cortico-thalamo-cortical circuit, in which the sensory processing mechanisms of different modalities modulate one another via the non-lemniscal sensory thalamus, we propose a novel cortico-thalamo-cortical neural network (CTCNet) for audio-visual speech separation (AVSS). First, the CTCNet learns hierarchical auditory and visual representations in a bottom-up manner in separate auditory and visual subnetworks, mimicking the functions of the auditory and visual cortical areas. Then, inspired by the large number of connections between cortical regions and the thalamus, the model fuses the auditory and visual information in a thalamic subnetwork through top-down connections. Finally, the model transmits this fused information back to the auditory and visual subnetworks, and the above process is repeated several times. The results of experiments on three speech separation benchmark datasets show that CTCNet remarkably outperforms existing AVSS methods with considerably fewer parameters. These results suggest that mimicking the anatomical connectome of the mammalian brain has great potential for advancing the development of deep neural networks.

Cortical Responses to Mother's Voice in Comparison with Unfamiliar Voice in the First Trimester of Life: A fNIRS Study.

Introduction The use of functional near-infrared light spectroscopy (fNIRS) may be applied to study cortical responses in children and could offer insight into auditory and speech perception during the early stages of life. Some literature suggests that babies are already able to identify familiar voices at birth, and fNIRS is a non-invasive technique that can be used to study this population. Objective To characterize the cortical responses of infants during their first trimester of life to infant-directed speech using near-infrared light spectroscopy and to verify whether there is a difference in responses when infant-directed speech is performed by their mother compared with an unknown person. Methods Twenty-three children between 0 and 3 months, healthy, without risk indicators for hearing loss, and with results considered normal in the audiological evaluation were tested with near-infrared spectroscopy using infant-directed speech as an auditory stimulus produced by their own mother and by an unknown source. Results Bilateral cortical activation was observed. The responses were present in the temporal, frontal, and parietal regions. Regarding the familiarity aspect, no significant difference was observed for the mother's voice compared with an unknown voice. Conclusion Infant-directed speech has prosodic characteristics capable of activating several cortical regions in the infant's first trimester of life, especially the temporal region. The familiarity effect needs to be better defined for this type of stimulus during this period.

State of the Art of Brain Function Detection Technologies in Robot-Assisted Lower Limb Rehabilitation.

Background: With an aging population, the prevalence of neurological disorders is increasing, leading to a rise in lower limb movement disorders and, in turn, a growing need for rehabilitation training. Previous neuroimaging studies have shown a growing scientific interest in the study of brain mechanisms in robot-assisted lower limb rehabilitation (RALLR). Objective: This review aimed to determine differences in neural activity patterns during different RALLR tasks and the impact on neurofunctional plasticity. Methods: Sixty-five articles in the field of RALLR were selected and tested using three brain function detection technologies. Results: Most studies have focused on changes in activity in various regions of the cerebral cortex during different lower limb rehabilitation tasks but have also increasingly focused on functional changes in other cortical and deep subcortical structures. Our analysis also revealed a neglect of certain task types. Conclusion: We identify and discuss future research directions that may contribute to a clear understanding of neural functional plasticity under different RALLR tasks. Impact Statement The evaluation of robot-assisted lower limb rehabilitation based on brain function detection technology can assess the neurological changes of patients in the rehabilitation process by monitoring brain activities and can also provide more accurate guidance for robot-assisted lower limb rehabilitation. By monitoring the patient's brain activity, the robot can adjust according to the real-time status of the patient to achieve more effective rehabilitation training. This has potential impact on improving the rehabilitation effect and speeding up the rehabilitation process of patients.

Structural and covariance network alterations of the hippocampus and amygdala in congenital hearing loss children

ObjectiveThe hippocampus and amygdala, as important components of the limbic system, play crucial roles in central remodeling in congenital hearing loss. This study aimed to investigate the morphological integrity and network properties of the subfields of hippocampus and amygdala in children with congenital hearing loss. MethodsA total of 24 children with congenital hearing loss and 17 age- and sex- matched healthy controls (HC) are included in the study. T1-weighted images are analyzed by segmenting the brain into cortical and subcortical regions. Intergroup difference of volumes were explored. Structural covariance networks for the whole brain and hippocampus-amygdala subregions were constructed. Between-group differences of network property are investigated by comparing area under a range of network sparsity. ResultsPatients with congenital hearing loss exhibited significantly larger volumes in the right dentate gyrus and CA3 of the hippocampus. However, there were no significant differences in total hippocampal or showed decreased global efficiency and increased characteristic path length, indicating reduced network integration. Lower betweenness centrality was observed in the left hippocampal fissure in the hearing loss group. The changes in volume and network topological properties are not affected by age and sex. ConclusionChildren with congenital hearing loss display specific volumetric increases in hippocampal subregions, suggesting compensatory adaptations to auditory deprivation. The hippocampus-amygdala network shows significant reorganization, potentially underpinning cognitive and behavioral development issues associated with congenital hearing loss. These findings highlight the importance of targeted neural substrates in understanding and addressing the developmental challenges faced by children with congenital hearing loss.

Prophylactic (R,S)-ketamine and (2S,6S)-HNK decrease fear expression by differentially modulating fear neural ensembles

We previously reported that a single injection of (R,S)-ketamine or its metabolite (2S,6S)-hydroxynorketamine (HNK) prior to stress attenuates learned fear. However, whether these drugs attenuate learned fear through divergent or convergent effects on neural activity remains to be determined. 129S6/SvEv male mice were injected with saline, (R,S)-ketamine, or (2S,6S)-HNK one week before a 3-shock contextual fear conditioning (CFC) paradigm. Five days later, mice were re-exposed to the aversive context, and euthanized one hour later to quantify active cells. Brains were processed for c-fos immunoreactivity, and neural networks were built with a novel, wide-scale imaging pipeline. We found that (R,S)-ketamine and (2S,6S)-HNK attenuate learned fear. Fear-related neural activity was altered in: dorsal CA3 following (2S,6S)-HNK; ventral CA3 and CA1, infralimbic (IL) and prelimbic (PL) regions, insular cortex (IC), retrosplenial cortex (RSP), piriform cortex (PIR), nucleus reuniens (RE), and periaqueductal grey (PAG) following both (R,S)-ketamine and (2S,6S)-HNK; and in the paraventricular nucleus of thalamus (PVT) following (R,S)-ketamine. Dorsal CA3 and ventral hippocampus activation correlated with freezing in the (R,S)-ketamine group, and RSP activation correlated with freezing in both (R,S)-ketamine and (2S,6S)-HNK groups. (R,S)-ketamine increased connectivity between cortical and subcortical regions while (2S,6S)-HNK increased connectivity within these regions. This work identifies novel nodes in fear networks, involving the RE, PIR, IC, PAG and RSP, that can be targeted with neuromodulatory strategies or pharmaceutical compounds to treat fear-induced disorders. This approach could be used to optimize target engagement and dosing strategies of existing medications.

Fitness, Gray Matter Volume, and Executive Function in Cognitively Normal Older Adults: Cross-Sectional Findings From the AGUEDA Trial.

The aim of the study is to investigate the association of cardiorespiratory fitness (CRF) and muscular strength indicators with gray matter volume (GMV) and to study whether fitness-related regions of GMV are associated to executive function (EF) in cognitively normal older adults. Ninety-one cognitively normal older adults (71.69 ± 3.91 years; 57.14% females) participated in this study from the AGUEDA trial. CRF was measured by a 2-km walking test and a 6-min walking test. Muscular strength was measured by handgrip, biceps curl, squats, and isokinetic strength tests. T1-weigthed images were obtained through a magnetic resonance scan. GMV was determined by voxel-based morphometric analysis. Standardized EF tests were performed. CRF did not show any positive association with GMV. Handgrip strength was positively associated with GMV (p < 0.001) in nine regions (β from 0.6 to 0.8 and k from 106 to 1927) and knee extension strength in three regions (β from 0.4 to 0.5 and k from 76 to 2776). Squats strength was negatively associated with GMV (p < 0.001) in two regions (β = -0.3, k = 1102 and k = 152) and the 2-km walking test in one region (β = -0.4, k = 99). Only handgrip strength-related GMV was associated with cognitive flexibility (p = 0.039, β = 0.215) and spatial working memory (p < 0.03, β 0.247-0.317), but not with EF score (p > 0.05). Muscular strength, but no CRF, may be positively related to GMV in cortical and subcortical regions, with implications for specific cognitive domains rather than the overall EF score. Specifically, handgrip strength was the indicator most associated with higher GMV, while squats strength and CRF were negatively related to GMV. ClinicalTrials.gov identifier: NCT05186090.

Speech motor impairment in ALS is associated with multiregional cortical thinning beyond primary motor cortex.

Cortical thinning is well-documented in individuals with amyotrophic lateral sclerosis (ALS), yet its association with speech deterioration remains understudied. This study characterizes anatomical changes in the brain within the context of speech impairment patterns in individuals with ALS, providing insight into the disease's multiregional spread and biology. To evaluate patterns of cortical thickness in speakers with ALS with and without functional speech changes compared to healthy controls (HCs) using whole-brain and region of interest (ROI) analyses. Forty individuals with ALS and 22 HCs underwent a T1-weighted 3-Tesla magnetic resonance imaging (MRI). Individuals with ALS were divided into two groups based on the preserved speech [ps-ALS] (n = 18) or deteriorated speech [ds-ALS] (n = 22) as measured by the ALSFRSF-R speech subscore (=4 or <4 points, respectively). Sixteen a priori-defined and automatically segmented cortical and subcortical brain ROIs were selected based on their previously documented roles in speech production. Two cortical thickness analyses were performed: (1) group-level whole-brain surface-based analyses and (2) group-level ROI analyses. A case study of 6 ALS individuals examined the cortical thickness, and their speech was characterized using quantitative and qualitative measures. Based on the group-level whole-brain surface-based analyses, the ds-ALS group demonstrated significant cortical thinning compared to HCs in the left primary motor and somatosensory cortices and the right inferior parietal lobe with its adjacent lateral occipital cortical regions. The ps-ALS group demonstrated no significant cortical thinning compared to HCs. Based on the group-level ROI analyses, the ds-ALS group demonstrated significant cortical thinning compared to HCs in bilateral middle motor cortices, right posterior dorsal premotor cortex, and left anterior cingulate cortex. The case study analysis revealed that ALS speakers with speech features characteristic of spastic dysarthria exhibited cortical thinning, while those with speech features characteristic of flaccid dysarthria did not. Individuals with ALS have anatomical changes involving multiregional neocortical areas beyond the primary motor cortex that may manifest as subjective (i.e., clinical judgment) and objective (i.e., speaking rate) changes in speech production. Further longitudinal work in ALS is needed to better understand the link between MRI cortical thickness changes and bulbar dysfunction.

Distinct regional vulnerability to Aβ and iron accumulation in post mortem AD brains.

The paramagnetic iron, diamagnetic amyloid beta (Aβ) plaques and their interaction are crucial in Alzheimer's disease (AD) pathogenesis, complicating non-invasive magnetic resonance imaging for prodromal AD detection. We used a state-of-the-art sub-voxel quantitative susceptibility mapping method to simultaneously measure Aβ and iron levels in post mortem human brains, validated by histology. Further transcriptomic analysis using Allen Human Brain Atlas elucidated the underlying biological processes. Regional increased paramagnetic and diamagnetic susceptibility were observed in medial prefrontal, medial parietal, and para-hippocampal cortices associated with iron deposition (R=0.836, p=0.003) and Aβ accumulation (R=0.853, p=0.002) in AD brains. Higher levels of gene expression relating to cell cycle, post-translational protein modifications, and cellular response to stress were observed. These findings provide quantitative insights into the variable vulnerability of cortical regions to higher levels of Aβ aggregation, iron overload, and subsequent neurodegeneration, indicating changes preceding clinical symptoms. The vulnerability of distinct brain regions to amyloid beta (Aβ) and iron accumulation varies. Histological validation was performed on stained sections of ex-vivo human brains. Regional variations in susceptibility were linked to gene expression profiles. Iron and Aβ levels in ex-vivo brains were simultaneously quantified.

Human α-synuclein aggregation activates ferroptosis leading to parvalbumin interneuron degeneration and motor learning impairment.

The accumulation of α-synuclein induces neuronal loss in midbrain nuclei and leads to the disruption of motor circuits, while the pathology of α-synuclein in cortical regions remains elusive. To better characterize cortical synucleinopathy, here we generate a mouse model with the overexpression of human α-synuclein in the primary motor cortex (M1) of mice. A combination of molecular, in vivo recording, and behavioral approaches reveal that cortical expression of human α-synuclein results in the overexcitation of cortical pyramidal neurons (PNs), which are regulated by the decreased inhibitory inputs from parvalbumin-interneurons (PV-INs) to impair complex motor skill learning. Further mechanistic dissections reveal that human α-synuclein aggregation activates ferroptosis, contributing to PV-IN degeneration and motor circuit dysfunction. Taken together, the current study adds more knowledge to the emerging role and pathogenic mechanism of ferroptosis in neurodegenerative diseases.

Structural development and brain asymmetry in the fronto-limbic regions in preschool-aged children.

Early-life experiences play a crucial role in the development of the fronto-limbic regions, influencing both macro- and microstructural changes in the brain. These alterations profoundly impact cognitive, social-emotional functions. Recently, early limbic structural alterations have been associated with numerous neurological and psychiatric morbidities. Although identifying normative developmental trajectories is essential for determining brain alterations, only a few studies have focused on examining the normative trajectories in the fronto-limbic regions during preschool-aged children. The aim of this study was to investigate the structural-developmental trajectory of the fronto-limbic regions using the cortical thickness, volume, and subcortical volume in 57 healthy and typical preschool-aged children between 1 and 5 years and examined the early lateralization patterns during the development of the fronto-limbic regions. Regarding brain lateralization, remarkable asymmetry was detected in the volume of thalamus and the cortical regions excluding the lateral orbitofrontal cortex in the fronto-limbic regions. This study of preschool-aged children may fill the knowledge gaps regarding the developmental patterns and hemispheric asymmetries of the fronto-limbic regions between newborns and adolescents.

A cortical field theory – dynamics and symmetries

We characterise cortical dynamics using partial differential equations (PDEs), analysing various connectivity patterns within the cortical sheet. This exploration yields diverse dynamics, encompassing wave equations and limit cycle activity. We presume balanced equations between excitatory and inhibitory neuronal units, reflecting the ubiquitous oscillatory patterns observed in electrophysiological measurements. Our derived dynamics comprise lowest-order wave equations (i.e., the Klein-Gordon model), limit cycle waves, higher-order PDE formulations, and transitions between limit cycles and near-zero states. Furthermore, we delve into the symmetries of the models using the Lagrangian formalism, distinguishing between continuous and discontinuous symmetries. These symmetries allow for mathematical expediency in the analysis of the model and could also be useful in studying the effect of symmetrical input from distributed cortical regions. Overall, our ability to derive multiple constraints on the fields — and predictions of the model — stems largely from the underlying assumption that the brain operates at a critical state. This assumption, in turn, drives the dynamics towards oscillatory or semi-conservative behaviour. Within this critical state, we can leverage results from the physics literature, which serve as analogues for neural fields, and implicit construct validity. Comparisons between our model predictions and electrophysiological findings from the literature — such as spectral power distribution across frequencies, wave propagation speed, epileptic seizure generation, and pattern formation over the cortical surface — demonstrate a close match. This study underscores the importance of utilizing symmetry preserving PDE formulations for further mechanistic insights into cortical activity.

Abnormal beta bursts of depression in the orbitofrontal cortex and its relationship with clinical symptoms

BackgroundRecent researches have reported that frequency-specific patterns of neural activity contain not only rhythmically sustained oscillations but also transient-bursts of isolated events. The aim of this study was to investigated the correlation between beta burst and depression in order to explore depressive disease and the neurological underpinnings of disease-related symptoms. MethodsWe collected resting-state MEG recordings from 30 depressive patients and a matched 40 healthy controls. A Hidden Markov Model (HMM) was applied on source-space time courses for 78 cortical regions of the AAL atlas and the temporal characteristics of beta burst from the matched HMM states were captured. Group differences were evaluated on these beta burst characteristics after permutation tests and, for the depressive group, associations between burst characteristics and clinical symptom severity were determined using Spearman correlation coefficients. ResultsAt a threshold of p=0.05corrected, burst characteristics revealed significant differences between depression patients and controls at the group level, including increased burst amplitude in frontal lobe, decreased burst duration in occipital regions, increased burst rate and decreased burst interval time in some brain regions. Furthermore, burst amplitude in the orbitofrontal cortex (OFC) was positively related to the severity of sleep disturbance and burst rate in the OFC was negatively related to the severity of anxiety in depression patients. ConclusionsThe findings highlight OFC may be a targeted area responsible for the anxiety and sleep disturbance symptom by abnormal beta burst in depressive patients and beta burst characteristics of OFC might serve as a neuro-marker for the depression.