Brain Regions Research Articles

Seven-tesla magnetic resonance imaging of the nervus terminalis, olfactory tracts, and olfactory bulbs in COVID-19 patients with anosmia and hypogeusia

IntroductionLinking olfactory epithelium to the central nervous system are cranial nerve 1, the olfactory nerve, and cranial nerve “0,” and the nervus terminalis (NT). Since there is minimal expression of angiotensin-converting enzyme-2 (ACE-2) in the olfactory nerve, it is unclear how SARS-CoV-2 causes anosmia (loss of smell) and hypogeusia (reduction of taste). In animal models, NT expresses ACE-2 receptors, suggesting a possible SARS-CoV-2 viral entry site in humans. The purpose of this study was to determine whether ultra-high-field 7 T magnetic resonance imaging (MRI) could visualize the NT, olfactory bulbs (OB), and olfactory tract (OT) in healthy controls and COVID-19 anosmia or hypogeusia and to qualitatively assess for volume loss and T2 alterations.MethodsIn this study, 7 T MRI was used to evaluate the brain and olfactory regions in 45 COVID-19 patients and 29 healthy controls. Neuroimaging was qualitatively assessed by four board-certified neuroradiologists who were blinded to outcome assignments: for the presence or absence of NT; for OB, OT, and brain volume loss; and altered T2 signal, white matter T2 hyperintensities, microhemorrhages, enlarged perivascular spaces, and brainstem involvement.ResultsNT was identifiable in all COVID-19 patients and controls. T2 hyperintensity in the NT, OB, and OT in COVID-19 patients with anosmia or hypogeusia was statistically significant compared to controls and COVID-19 patients without anosmia or hypogeusia.DiscussionOn 7 T MRI, NT was radiographically identifiable, adjacent to OB and OT. In COVID-19 anosmia and hypogeusia, T2 hyperintensity of NT, OB, and OT was statistically significant compared to COVID-19 patients without anosmia or hypogeusia and controls. The NT may be a potential entry site for SARs-CoV-2 and may play a role in the pathophysiology of COVID-19 anosmia.

Basolateral amygdala inputs to the nucleus accumbens shell modulate the consolidation of cued-response and inhibitory avoidance learning

The basolateral amygdala (BLA) modulates different types of memory consolidation via distinct projections to downstream brain regions in multiple memory systems. Prior studies indicate that the BLA projects to the nucleus accumbens shell (NAshell) and that these regions interact to influence some types of behavior. Moreover, previous pharmacological work suggests the BLA and NAshell interact to influence memory. However, the precise role of the BLA-NAshell pathway has never been directly investigated in the consolidation of different types of memory including cued-response, spatial, or inhibitory avoidance (IA) learning. To address this, male and female Sprague-Dawley rats received optogenetic manipulations of the BLA or BLA-NAshell pathway immediately following training in different learning tasks. An initial experiment found that optogenetically inhibiting the BLA itself immediately after training impaired cued-response retention in a Barnes maze task in males and females, confirming earlier pharmacological work in males alone. Subsequent experiments found that BLA-NAshell pathway inhibition impaired retention of cued-response and IA learning but had no effect on retention of spatial learning. However, the present work did not observe any effects of pathway stimulation immediately after cued-response or IA learning. Together, the present findings suggest the BLA modulates the consolidation of cued-response and IA, but not spatial, memory consolidation via NAshell projections.

Sex differences in gray matter, white matter, and regional brain perfusion in young, healthy adults.

Cerebrovascular and neurological diseases exhibit sex-specific patterns in prevalence, severity, and regional specificity, some of which are associated with altered cerebral blood flow (CBF). Females often exhibit higher resting CBF, but understanding the impact of sex per se on CBF is hampered by study variability in age, comorbidities, medications, and control for menstrual cycle or hormone therapies. A majority of studies report whole brain CBF without differentiating between gray and white matter or without assessing regional CBF. Thus fundamental sex differences in regional or whole brain CBF remain unclarified. While controlling for the above confounders, we tested the hypothesis that females will exhibit higher total gray and white matter perfusion as well as regional gray matter perfusion. Adults 18-30 yr old (females = 22 and males = 26) were studied using arterial spin labeling (ASL) magnetic resonance imaging (MRI) scans followed by computational anatomy toolbox (CAT12) analysis in statistical parametric mapping (SPM12) to quantify CBF relative to brain volume. Females displayed 40% higher perfusion globally (females = 62 ± 9 and males = 45 ± 10 mL/100 g/min, P < 0.001), gray matter (females = 75 ± 11 and males = 54 ± 12 mL/100 g/min, P < 0.001), and white matter (females = 44 ± 6 and males = 32 ± 7 mL/100 g/min, P < 0.001). Females exhibited greater perfusion than males in 67 of the 68 regions tested, ranging from 14% to 66% higher. A second MRI approach (4-dimensional flow) focused on large arteries confirmed the sex difference in global CBF. These data indicate strikingly higher basal CBF in females at global, gray, and white matter levels and across dozens of brain regions and offer new clarity into fundamental sex differences in global and regional CBF regulation before aging or pathology.NEW & NOTEWORTHY MRI used to measure cerebral blood flow (CBF) in gray matter, white matter, and 68 regions in healthy men and women. This study demonstrated that CBF is 40% higher in women, the highest sex difference reported, when controlling for numerous important clinical confounders like age, smoking, menstrual cycle, comorbidities, and medications.

The Influence of Structural Brain Changes on Cognition in the Context of Healthy Aging: Exploring Mediation Effects Through gBAT-The Graphical Brain Association Tool.

The contribution of age-related structural brain changes to the well-established link between aging and cognitive decline is not fully defined. While both age-related regional brain atrophy and cognitive decline have been extensively studied, the specific mediating role of age-related regional brain atrophy on cognitive functions is unclear. This study introduces an open-source software tool with a graphical user interface that streamlines advanced whole-brain mediation analyses, enabling researchers to systematically explore how the brain acts as a mediator in relationships between various behavioral and health outcomes. The tool is showcased by investigating regional brain volume as a mediator to determine the contribution of age-related brain volume loss toward cognition in healthy aging. We analyzed regional brain volumes and cognitive testing data (Montreal Cognitive Assessment [MoCA]) from a cohort of 131 neurologically healthy adult participants (mean age 50 ± 20.8 years, range 20-79, 73% females) drawn from the Aging Brain Cohort Study at the University of South Carolina. Using our open-source tool developed for evaluating brain-behavior associations across the brain and optimized for exploring mediation effects, we conducted a series of mediation analyses using participant age as the predictor variable, total MoCA and MoCA subtest scores as the outcome variables, and regional brain volume as potential mediators. Age-related atrophy within specific anatomical networks was found to mediate the relationship between age and cognition across multiple cognitive domains. Specifically, atrophy in bilateral frontal, parietal, and occipital areas, along with widespread subcortical regions mediated the effect of age on total MoCA scores. Various MoCA subscores were influenced by age through atrophy in distinct brain regions. These involved prefrontal regions, sensorimotor cortex, and parieto-occipital areas for executive function subscores, prefrontal and temporo-occipital regions, along with the caudate nucleus for attention and concentration subscores, frontal and parieto-occipital areas, alongside connecting subcortical areas such as the optic tract for visuospatial subscores and frontoparietal areas for language subscores. Brain-based mediation analysis offers a causal framework for evaluating the mediating role of brain structure on the relationship between age and cognition and provides a more nuanced understanding of cognitive aging than previously possible. By validating the applicability and effectiveness of this approach and making it openly available to the scientific community, we facilitate the exploration of causal mechanisms between variables mediated by the brain.

Neuro-cognitive effects of degraded visibility on illusory body ownership

Based on visuo-tactile stimulation, the rubber hand illusion induces a sense of ownership for a dummy hand. Manipulating the visibility of the dummy hand during the stimulation influences cognitive aspects of the illusion, suggesting that the related brain activity may be influenced too. To test this, we analyzed brain activity (fMRI), subjective ratings, and skin conductance from 45 neurotypical participants undergoing a modified rubber hand illusion protocol where we manipulated the visibility (high, medium, and low) of a virtual hand, not the brush (virtual hand illusion; VHI). To further investigate the impact of visibility manipulations on VHI-related secondary effects (i.e. vicarious somatosensation), we recorded brain activity and skin conductance during a vicarious pain protocol (observation of painful stimulations of the virtual hand) that occurred after the VHI procedure. Results showed that, during both the VHI and vicarious pain periods, the activity of distinct visual, somatosensory, and motor brain regions was modulated by (i) visibility manipulations, (ii) coherence between visual and tactile stimulation, and (iii) time of visuo-tactile stimulation. Accordingly, embodiment-related subjective ratings of the perceived illusion were specifically influenced by visibility manipulations. These findings suggest that visibility modifications can impact the neural and cognitive effects of illusory body ownership, in that when visibility decreases the illusion is perceived as weaker and the brain activity in visual, motor, and somatosensory regions is overall lower. We interpret this evidence as a sign of the weight of vision on embodiment processes, in that the cortical and subjective aspects of illusory body ownership are weakened by a degradation of visual input during the induction of the illusion.

Quantitative comparison of CSVD imaging markers between patients with possible amyloid small vessel disease and with non-amyloid small vessel disease

The spatial distribution patterns of cerebral microbleeds are associated with different types of cerebral small vessel disease (CSVD). This study aims to examine the disparities in brain imaging markers of CSVD among patients diagnosed with possible amyloid and non-amyloid small vessel disease. The head MR scans including susceptibility-weighted imaging (SWI) sequences from 351 patients at our institute were collected for analysis. CSVD imaging markers were quantified or graded across various CSVD dimensions in the patient images. Patients were categorized into the cerebral amyloid angiopathy group (CAA), hypertensive arteriopathy group (HA), or mixed small vessel disease group (Mixed), based on the spatial distribution of microbleeds. White matter lesions (WML) were segmented using an artificial neural network and assessed via a voxel-wise approach. Significant differences were observed among the three groups in several indices: microbleed count, lacune count at the centrum semiovale and basal ganglia levels, grade of enlarged perivascular space (EPVS) at the basal ganglia, and white matter lesion volume. These indices were substantially higher in the Mixed group compared to the other groups. Additionally, the incidences of cerebral hemorrhages (χ2 = 7.659, P = 0.006) and recent small subcortical infarcts (χ2 = 4.660, P = 0.031) were significantly more frequent in the HA group than in the CAA group. These results indicate that mixed spatial distribution patterns of microbleeds demonstrated the highest burden of cerebral small vessel disease. Microbleeds located in the deep brain regions were associated with a higher incidence of recent small subcortical infarcts and cerebral hemorrhages compared to those in the cortical areas.

Brains in sync, friends in empathy: interbrain neural mechanisms underlying the impact of interpersonal closeness on mutual empathy.

Many everyday empathetic experiences arise within our social interactions and depend significantly on interpersonal closeness. However, the interbrain processes underlying social-oriented empathy by interpersonal closeness remain unclear. To address this gap, we conducted a dyadic social judgement task with dyads of friends and strangers, where targets received social evaluative feedback and empathizers observed the scenario in different experimental trials. Results showed that dyads of friends exhibited greater affect sharing than strangers when witnessing their partners being accepted or rejected. This was supported by the more pronounced event-related potential similarity in friends during the 340-840 ms post-feedback window, mediating the link between interpersonal closeness and affect sharing. Furthermore, witnessing emotional feedback elicited greater interbrain neural synchronization of brain α-oscillation between the empathizer's left prefrontal cortex and the target's left temporoparietal junction in dyads of friends compared with those of strangers. This empathy-related synchronization was associated with mutual affect sharing within dyads of friends but not within dyads of strangers. Our findings highlight the sensitivity of empathy to interpersonal closeness, which links to sustained attention and detailed evaluation in social scenarios, along with functional communication between brain regions for mentalizing and emotional regulation. These insights have therapeutic potential for improving social functioning and relationship satisfaction.

Advancing research on odor-induced sweetness enhancement: A EEG local-global fusion transformer network for sweetness quantification combined with EEG technology

Reducing sugar intake is crucial for health, and odor sweetening enhances food enjoyment and quality perception. Current research relies on subjective manual sensory evaluations, which are poorly reproducible. Traditional methods also fail to capture dynamic neural responses to odor-induced sweetness. We propose an electroencephalogram local-global fusion transformer network (EEG-LGFNet) model to decode this impact objectively. Electroencephalogram data were collected from 16 subjects under different odor and sucrose stimuli. The model captures complex neural signals by integrating local and global feature extraction mechanisms. Its performance was validated across three-time windows, demonstrating efficacy over various temporal ranges. Analysis of the coefficient of determination across brain regions confirmed the importance of the frontal, central, and parietal areas of sweetness perception. The EEG-LGFNet model excelled in quantifying odor-enhanced sweetness, significantly outperforming state-of-the-art models. This research offers new insights into odor sweetening, with applications in food development, personalized nutrition, and neuroscience.

Impact of levetiracetam and ethanol on memory, selected neurotransmitter levels, oxidative stress parameters, and essential elements in rats.

Ethanol disrupts brain activity and memory. There is evidence supporting the beneficial effect of levetiracetam on alcohol consumption. Therefore, the aim of the study was to examine whether levetiracetam has a protective activity against ethanol-induced memory impairment, alterations in selected neurotransmission activities, oxidative stress, and selected essential elements in rats. The rats were given levetiracetam (300mg/kg b.w. po) with ethanol for three weeks prior to behavioral tests. Spatial memory was tested using the Morris water maze, while recognition memory was evaluated using the Novel object recognition test. The GABA and glutamate concentration was determined in three rat brain regions (cerebellum, hippocampus, and cerebral cortex). Serum oxidative stress parameters and selected essential elements concentration (Cu, Mn, Zn, Fe, Mg) in the rat brain were analyzed. Levetiracetam administered with ethanol improved spatial memory, but did not affect abstinence-induced impairment. The drug also decreased ethanol-induced long-term recognition memory impairment. No alterations in glutamate levels were observed. GABA levels were elevated by levetiracetam in the cerebral cortex and by ethanol in the cerebellum. Ethanol increased catalase activity (CAT) and decreased superoxide dismutase activity (SOD) in the serum. Levetiracetam significantly increased the activity of SOD. Alcohol disrupted the levels of trace elements (Mn, Zn, Mg) in the rat brain. Additionally, levetiracetam alone increased Mg, Fe, and Cu concentrations while all animals receiving the drug also had significantly lower concentrations of Zn. Levetiracetam had differential effects against ethanol-induced impairments. These findings could have important implications for future levetiracetam treatment in patients.

A Rose by Any Other Name: Mapping Taxonomic and Thematic Naming Errors Poststroke.

Understanding the neurobiology of semantic knowledge is a major goal of cognitive neuroscience. Taxonomic and thematic semantic knowledge are represented differently within the brain's conceptual networks, but the specific neural mechanisms remain unclear. Some neurobiological models propose that the anterior temporal lobe is an important hub for taxonomic knowledge, whereas the TPJ is especially involved in the representation of thematic knowledge. However, recent studies have provided divergent evidence. In this context, we investigated the neural correlates of taxonomic and thematic confrontation naming errors in 79 people with aphasia. We used three complementary lesion-symptom mapping (LSM) methods to investigate how structure and function in both spared and impaired brain regions relate to taxonomic and thematic naming errors. Voxel-based LSM mapped brain damage, activation-based LSM mapped BOLD signal in surviving tissue, and network-based LSM mapped white matter subnetwork integrity to error type. Voxel- and network-based lesion symptom mapping provided converging evidence that damage/disruption of the left mid-to-anterior temporal lobe was associated with a greater proportion of thematic naming errors. Activation-based lesion symptom mapping revealed that higher BOLD signal in the left anterior temporal lobe during an in-house naming task was associated with a greater proportion of taxonomic errors on the Philadelphia Naming Test administered outside of the scanner. A lower BOLD signal in the bilateral angular gyrus, precuneus, and right inferior frontal cortex was associated with a greater proportion of taxonomic errors. These findings provide novel evidence that damage to the anterior temporal lobe is especially related to thematic naming errors.

Lack variation of low slow-wave activity over time in the frontal region in NREM sleep may be associated with dyskinesia in Parkinson's disease.

Levodopa-induced dyskinesia (DYS) adversely affects the quality of life of Parkinson's disease (PD) patients. However, few studies have focused on the relationship between DYS and sleep and electroencephalography (EEG). Our study aimed to establish the objective physiological indicators assessed by polysomnography (PSG) that are associated with DYS in PD patients. We enrolled 122 patients with PD, divided into two groups: PD with DYS (n = 27) and PD without DYS group (non-DYS, n = 95). The demographics and clinical characteristics and sleep assessment in the two groups were collected. More importantly, overnight six-channel PSG parameters were compared in the two groups. We also compared different bands and brain regions of average power spectral density within each group. Compared with the non-DYS group, the DYS group tended to have a significantly higher percentage of nonrapid eye movement sleep (NREM). Gender, levodopa equivalent daily dose (LEDD), rapid eye movement (REM) sleep (min), and the NREM percentage were positively correlated with the occurrence of DYS. After adjusting for gender, disease duration, LEDD, taking amantadine or not, and Montreal Cognitive Assessment (MoCA), NREM%, N3%, and REM (min), the percentage of NREM sleep (p = 0.035), female (p = 0.002), and LEDD (p = 0.005), and REM sleep time (min) (p = 0.012) were still associated with DYS. There was no significant difference in whole-night different bands of average power spectral density between two groups. There was no significant difference in normalized average power spectral density of slow wave activity (SWA) (0.5-2 Hz, 0.5-4 Hz, and 2-4 Hz) of early and late NREM sleep in the DYS group. Dynamic normalized average power spectral density of SWA of low-frequency (0.5-2 Hz) reduction in the frontal region (p = 0.013) was associated with DYS in logistic regression after adjusting for confounding factors. PD patients with DYS have substantial sleep structure variations. Higher NREM percentage and less REM percentage were observed in PD patients with DYS. Dynamic normalized average power spectral density of low-frequency (0.5-2 Hz) SWA reduction in the frontal area could be a new electrophysiological marker of DYS in PD.

Insula-Medial Prefrontal Cortex Functional Connectivity Modulated by Transcutaneous Auricular Vagus Nerve Stimulation: An fMRI Study.

Transcutaneous auricular vagus nerve stimulation (taVNS) is an emerging neuromodulation technology that has been reported to be beneficial in the treatment of diseases by several studies, but its exact mechanism of action is still unclear. It has been demonstrated that taVNS can influence interoceptive signals. Notably, the processing of interoceptive signals is directly related to many diseases, such as depression, anxiety, and insomnia. The insula and the medial prefrontal cortex (MPFC) communicate during the bottom-up transmission of taVNS-induced signals, and both play a role in interoceptive signal processing. By focusing on the insula and MPFC, our research pioneers detail the potential interactions between interoceptive signal processing and the neuromodulation effects of taVNS, providing novel insights into the neurobiological mechanisms of taVNS. Two functional connectivity (FC) analyses (region of interest-based and seed-based) were used in this study. We observed that negative connectivity between the insula and the MPFC was significantly weakened following taVNS, while there were no statistical changes in the sham group. Our findings elucidate potential mechanisms linking vagal activity with intrinsic FC among specific brain regions and networks. Specifically, our results indicate that taVNS may enhance the ability to flexibly balance interoceptive awareness and cognitive experiences by modulating the FC between the insula and MPFC. The modulation effects may impact body-brain interactions, suggesting the mechanism of taVNS in therapeutic applications.

Identifying Brain Network Structure for an fMRI Effective Connectivity Study Using the Least Absolute Shrinkage and Selection Operator (LASSO) Method

Background: Studying causality relationships between different brain regions using the fMRI method has attracted great attention. To investigate causality relationships between different brain regions, we need to identify both the brain network structure and the influence magnitude. Most current methods concentrate on magnitude estimation, but not on identifying the connection or structure of the network. To address this problem, we proposed a nonlinear system identification method, in which a polynomial kernel was adopted to approximate the relation between the system inputs and outputs. However, this method has an overfitting problem for modelling the input–output relation if we apply the method to model the brain network directly. Methods: To overcome this limitation, this study applied the least absolute shrinkage and selection operator (LASSO) model selection method to identify both brain region networks and the connection strength (system coefficients). From these coefficients, the causality influence is derived from the identified structure. The method was verified based on the human visual cortex with phase-encoded designs. The functional data were pre-processed with motion correction. The visual cortex brain regions were defined based on a retinotopic mapping method. An eight-connection visual system network was adopted to validate the method. The proposed method was able to identify both the connected visual networks and associated coefficients from the LASSO model selection. Results: The result showed that this method can be applied to identify both network structures and associated causalities between different brain regions. Conclusions: System identification with LASSO model selection algorithm is a powerful approach for fMRI effective connectivity study.

The Interplay between MiR-134/BDNF and LKB1/AMPK/SIRT1 Accentuates the Antidepressant Efficacy of Empagliflozin in Ovariectomized Rats.

Major depressive disorder (MDD) is considered a major cause of suicide worldwide. As previous studies revealed that neuroinflammation is a significant factor in the etiology of MDD, this study proposed to unravel the possible antidepressant effect of Empagliflozin (EMPA) through targeting miRNA-134 (miR-134)/brain-derived neurotrophic factor (BDNF) and liver kinase B1 (LKB1)/adenosine 5'-monophosphate-activated protein kinase (AMPK)/silent information regulator 1 (SIRT1) axes in ovariectomized (OVX) female rats. Rats were assigned randomly to four groups: Sham operation (SO), OVX, OVX + EMPA (10 mg/kg/day, p.o.), and OVX + EMPA + Dorsomorphin (DORSO) (25 μg/day/rat, i.v.). Drugs were administered for 28 days after 2 weeks of surgery. EMPA debilitated OVX-induced depressive-like behavior by mitigating the immobility time in the tail suspension test and forced swimming test. Moreover, EMPA curtailed OVX-induced alterations of serum estradiol, hippocampal serotonin, miR-134 expression, as well as BDNF. EMPA also dwindled OVX-induced changes of hippocampal p-LKB1/LKB1, p-AMPK/AMPK, SIRT1, and inflammatory markers (nuclear factor-kappa-B, interleukin-1 beta, interleukin-6, and tumor necrosis factor alpha). Additionally, the EMPA-treated group exhibited marked improvement in different brain regions' histopathology. However, DORSO coadministration reversed most of EMPA's beneficial effects. The current study displayed the modulatory role of EMPA on miR-134/BDNF and LKB1/AMPK/SIRT1 axes, thus offering a partial explanation of its antidepressant efficacy and proposing EMPA as a novel therapeutic avenue for MDD.

Linear Monotonic Inter-electrode Associations as Quantitative EEG for Alcoholism Diagnosis

Alcohol use disorders (AUDs) are associated with alterations in EEG patterns that reflect underlying neural dysfunctions, such as impaired cognitive processing, reduced neural connectivity, and disrupted brain rhythms. These EEG alterations can be indicative of several brain disorders, including cognitive deficits, mood disorders, and neurodegenerative diseases, which are often exacerbated by chronic alcohol abuse. Cognitive impairment in alcoholic subjects is caused due to altered functional connectivity between brain regions that can be quantified using statistical measures such as correlation. This paper proposes novel Quantitative EEG (QEEG) features comprising the band-wise absolute value of inter-electrode correlations as a measure of brain functional connectivity to classify alcoholic and non-alcoholic EEG. The EEG signal is first decomposed into five frequency sub-bands. In each sub-band, the absolute value of the linear Pearson product-moment correlation coefficient is computed between time-series EEG recorded by electrode pairs placed over different brain regions. To reduce the dimensionality of the feature vector, an ensemble feature selection approach is adopted, utilizing ANOVA and Chi-square, in conjunction with greedy forward feature selection wrapper algorithm. Four classifiers, namely SVM, KNN, ANN and RF are utilized for the classification. Among them, the SVM classifier achieves the best classification accuracies of 100% on validation with test data and 99.58% on cross-validation with train data, respectively.

Comparative analysis of electroencephalogram (EEG) data gathered from the frontal region with other brain regions affected by attention deficit hyperactivity disorder (ADHD) through multiresolution analysis and machine learning techniques

Attention deficit hyperactivity disorder (ADHD) is a neurodevelopmental disorder characterized by repeated patterns of hyperactivity, impulsivity, and inattention that limit daily functioning and development. Electroencephalography (EEG) anomalies correspond to changes in brain connection and activity. The authors propose utilizing empirical mode decomposition (EMD) and discrete wavelet transform (DWT) for feature extraction and machine learning (ML) algorithms to categorize ADHD and control subjects. For this study, the authors considered freely accessible ADHD data obtained from the IEEE data site. Studies have demonstrated a range of EEG anomalies in ADHD patients, such as variations in power spectra, coherence patterns, and event-related potentials (ERPs). Some of the studies claimed that the brain’s prefrontal cortex and frontal regions collaborate in intricate networks, and disorders in either of them exacerbate the symptoms of ADHD. , Based on the research that claimed the brain’s prefrontal cortex and frontal regions collaborate in intricate networks, and disorders in either of them exacerbate the symptoms of ADHD, the proposed study examines the optimal position of EEG electrode for identifying ADHD and in addition to monitoring accuracy on frontal/ prefrontal and other regions of brain our study also investigates the position groupings that have the highest effect on accurateness in identification of ADHD. The results demonstrate that the dataset classified with AdaBoost provided values for accuracy, precision, specificity, sensitivity, and F1-score as 1.00, 0.70, 0.70, 0.75, and 0.71, respectively, whereas using random forest (RF) it is 0.98, 0.64, 0.60, 0.81, and 0.71, respectively, in detecting ADHD. After detailed analysis, it is observed that the most accurate results included all electrodes. The authors believe the processes can detect various neurodevelopmental problems in children utilizing EEG signals.

Analog Sequential Hippocampal Memory Model for Trajectory Learning and Recalling: A Robustness Analysis Overview

The rapid expansion of information systems in all areas of society demands more powerful, efficient, and low‐energy consumption computing systems. Neuromorphic engineering has emerged as a solution that attempts to mimic the brain to incorporate its capabilities to solve complex problems in a computationally and energy‐efficient way in real time. Within neuromorphic computing, building systems to efficiently store the information is still a challenge. Among all the brain regions, the hippocampus stands out as a short‐term memory capable of learning and recalling large amounts of information quickly and efficiently. Herein, a spike‐based bio‐inspired hippocampus sequential memory model is proposed that makes use of the benefits of analog computing and spiking neural networks (SNNs): noise robustness, improved real‐time operation, and energy efficiency. This model is applied to robotic navigation to learn and recall trajectories that lead to a goal position within a known grid environment. The model is implemented on the special‐purpose SNNs mixed‐signal DYNAP‐SE hardware platform. Through extensive experimentation together with an extensive analysis of the model's behavior in the presence of external noise sources, its correct functioning is demonstrated, proving the robustness and consistency of the proposed neuromorphic sequential memory system.

Local molecular and connectomic contributions of tau-related neurodegeneration.

Neurodegeneration in Alzheimer's disease (AD) is known to be mostly driven by tau neurofibrillary tangles. However, both tau and neurodegeneration exhibit variability in their distribution across the brain and among individuals, and the relationship between tau and neurodegeneration might be influenced by several factors. I aimed to map local molecular and connectivity characteristics that affect the association between tau pathology and neurodegeneration. The current study was conducted on the cross-sectional tau-PET and longitudinal T1-weighted MRI scan data of 186 participants from the ADNI dataset including 71 cognitively unimpaired (CU) and 115 mild cognitive impairment (MCI) individuals. Furthermore, the normative molecular profile of a region was defined using neurotransmitter receptor densities, gene expression, T1w/T2w ratio (myelination), FDG-PET (glycolytic index, glucose metabolism, and oxygen metabolism), and synaptic density. I found that the excitatory-inhibitory (E:I) ratio, myelination, synaptic density, glycolytic index, and functional connectivity are linked with deviation in the relationship between tau and neurodegeneration. Furthermore, there was spatial similarity between tau pathology and glycolytic index, synaptic density, and functional connectivity across brain regions. The current study demonstrates that the regional susceptibility to tau-related neurodegeneration is associated with specific molecular and connectomic characteristics of the affected neural systems. I found that the molecular and connectivity architecture of the human brain is linked to the different effects of tau pathology on downstream neurodegeneration.

Structural and transcriptional signatures of arithmetic abilities in children

Arithmetic ability is critical for daily life, academic achievement, career development, and future economic success. Individual differences in arithmetic skills among children and adolescents are related to variations in brain structures. Most existing studies have used hypothesis-driven region of interest analysis. To identify distributed brain regions related to arithmetic ability, we used data-driven cross-validated predictive models to analyze cross-sectional behavioral and structural MRI data in children and adolescents. The gray matter volume (GMV) of widespread brain regions reliably predicted arithmetic abilities measured by the Comprehensive Mathematical Abilities Test. Furthermore, we applied neuroimaging-transcriptome association analysis to explore transcriptional signatures associated with structural patterns of arithmetic ability. Structural patterns of arithmetic ability primarily correlated with transcriptional profiles enriched for genes involved in transmembrane transport and synaptic signaling. Our findings enhance our understanding of the neural and genetic mechanisms underlying children’s arithmetic ability and offer a practical predictor for arithmetic skills during development.

Proinflammatory immune cells disrupt angiogenesis and promote germinal matrix hemorrhage in prenatal human brain.

Germinal matrix hemorrhage (GMH) is a devastating neurodevelopmental condition affecting preterm infants, but why blood vessels in this brain region are vulnerable to rupture remains unknown. Here we show that microglia in prenatal mouse and human brain interact with nascent vasculature in an age-dependent manner and that ablation of these cells in mice reduces angiogenesis in the ganglionic eminences, which correspond to the human germinal matrix. Consistent with these findings, single-cell transcriptomics and flow cytometry show that distinct subsets of CD45+ cells from control preterm infants employ diverse signaling mechanisms to promote vascular network formation. In contrast, CD45+ cells from infants with GMH harbor activated neutrophils and monocytes that produce proinflammatory factors, including azurocidin 1, elastase and CXCL16, to disrupt vascular integrity and cause hemorrhage in ganglionic eminences. These results underscore the brain's innate immune cells in region-specific angiogenesis and how aberrant activation of these immune cells promotes GMH in preterm infants.