Brain Regions Research Articles

Effects of List-Mode-Based Intraframe Motion Correction in Dynamic Brain PET Imaging.

Motion is unavoidable in dynamic [18F]-MK6240 Positron Emission Tomography (PET) imaging, especially in Alzheimer's disease (AD) research requiring long scan duration. To understand how motion correction affects quantitative analysis, we investigated two approaches: II-MC, which corrects for both inter-frame and intra-frame motion, and IO-MC, which only corrects for inter-frame motion. These methods were applied to 83 scans from 34 subjects, and we calculated distribution volume ratios (DVR) using the multilinear reference tissue model with two parameters (MRTM2) in tau-rich brain regions. Most of the studies yielded similar DVR results for both II-MC and IO-MC. However, in one scan of an AD subject, the inferior temporal region showed 14% higher DVR with II-MC compared to IO-MC. This difference was reasonable given the AD diagnosis, although similar results were not observed in other regions. Although discrepancies between IO-MC and II-MC results were rare, they underscore the importance of incorporating intra-frame motion correction for more accurate and dependable PET quantitation, particularly in the context of dynamic imaging. These findings suggest that while the overall impact of intra-frame motion correction may be subtle, it can improve the reliability of longitudinal PET data, ultimately enhancing our understanding of tau protein distribution in AD pathology.

Distinct connectivity patterns between perception and attention-related brain networks characterize dyslexia: machine learning applied to resting-state fMRI

Diagnosis of dyslexia often occurs in late schooling years, leading to academic and psychological challenges. Furthermore, diagnosis is time-consuming, costly, and reliant on arbitrary cutoffs. On the other hand, automated algorithms hold great potential in medical and psychological diagnostics. The aim of the present study was to develop a machine learning tool for the detection of dyslexia in children based on the intrinsic connectivity patterns of different brain networks underlying perception and attention. Here, 117 children (8-12 years old; 58 females; 52 typical readers; TR and 65 children with dyslexia) completed cognitive and reading assessments and underwent 10 minutes of resting-state fMRI. Functional connectivity coefficients between 264 brain regions were used as features for machine learning. Different supervised algorithms were employed for classification of children with and without dyslexia. A classifier trained on dorsal attention network features exhibited the highest performance (accuracy .79, sensitivity .92, specificity .64). Auditory, visual, and fronto-parietal network-based classification showed intermediate accuracy levels (70-75%). These results highlight significant neurobiological differences in brain networks associated with visual attention between TR and children with dyslexia. Distinct neural integration patterns can differentiate dyslexia from typical development, which may be utilized in the future as a biomarker for the presence and/or severity of dyslexia.

ST-SHAP: A hierarchical and explainable attention network for emotional EEG representation learning and decoding

Background:Emotion recognition using electroencephalogram (EEG) has become a research hotspot in the field of human–computer interaction, how to sufficiently learn complex spatial–temporal representations of emotional EEG data and obtain explainable model prediction results are still great challenges. New methodIn this study, a novel hierarchical and explainable attention network ST-SHAP which combines the Swin Transformer (ST) and SHapley Additive exPlanations (SHAP) technique is proposed for automatic emotional EEG classification. Firstly, a 3D spatial–temporal feature of emotional EEG data is generated via frequency band filtering, temporal segmentation, spatial mapping, and interpolation to fully preserve important spatial–temporal-frequency characteristics. Secondly, a hierarchical attention network is devised to sufficiently learn an abstract spatial–temporal representation of emotional EEG and perform classification. Concretely, in this decoding model, the W-MSA module is used for modeling correlations within local windows, the SW-MSA module allows for information interactions between different local windows, and the patch merging module further facilitates local-to-global multiscale modeling. Finally, the SHAP method is utilized to discover important brain regions for emotion processing and improve the explainability of the Swin Transformer model. Results:Two benchmark datasets, namely SEED and DREAMER, are used for classification performance evaluation. In the subject-dependent experiments, for SEED dataset, ST-SHAP achieves an average accuracy of 97.18%, while for DREAMER dataset, the average accuracy is 96.06% and 95.98% on arousal and valance dimension respectively. In addition, import brain regions that conform to prior knowledge of neurophysiology are discovered via a data-driven approach for both datasets. Comparison with existing methods:In terms of subject-dependent and subject-independent emotional EEG decoding accuracies, our method outperforms several closely related existing methods. Conclusion:These experimental results fully prove the effectiveness and superiority of our proposed algorithm.

Identification of asymmetrical abnormalities in functional connectivity and brain network topology for migraine sufferers: A preliminary study based on resting-state fMRI data

Research on the neural mechanisms underlying brain asymmetry in patients with migraine patients using fMRI is insufficient. This study proposed using lateralized algorithms for functional connectivity and brain network topology and investigated changes in their lateralization in patients with migraine. In study 1, laterality indices of functional connectivity (LFunctionCorr) and brain network topological properties (LBetweennessCentrality, LDegree, and LStrength) were defined. Differences between migraineurs and normal subjects were compared at whole-brain, half-brain, and region levels. In study 2, laterality indices were used to classify migraine and were validated using independent samples and the segment method for repeatability. In study 3, abnormal brain regions related to migraine were extracted based on the classification results and differences analysis. Study 1 found no significant differences related to in for migraine at the whole-brain level; however, significant differences were identified at the half-brain level for the hemispheric lateralization of the LFunctionCorr, while 11 significantly different brain regions were also identified at the brain region level. Furthermore, the classification accuracy in study 2 was 0.9366. With repeated validation, the accuracy reached 0.8561. Furthermore, after extending the samples according to the segmentation strategy, the classification accuracies were improved to 0.9408 and 0.8585. Study 3 identified 10 crucial brain regions with asymmetrical specificity based on laterality indices distributed across the visual network, the frontoparietal control network, the default mode network, the salience/ventral attention network and the limbic system. The results revealed novel insights and avenues for research into the mechanisms of migraine asymmetry and showed that the laterality indices could be used as a potential diagnostic imaging marker for migraine.

Regional heterogeneity of cerebral blood flow immediately after the onset of ventricular pacing in anesthetized rats.

Selective distribution of cerebral blood flow (CBF) to vital brain regions likely occurs during rapid severe hypotension caused by tachyarrhythmia, but has not yet been demonstrated. In this study, we aimed to test the hypothesis that CBF is differentially preserved between brain regions depending on the degree of hypotension. In anesthetized rats, CBF was measured in the motor cortex (MC), medial prefrontal cortex, amygdala, thalamus, dorsal hypothalamus, hippocampus, ventral tegmental area, dorsolateral periaqueductal gray (dlPAG), and parabrachial nucleus (PB) by using laser-Doppler flowmetry. Ventricular pacing was performed for 30 s at 550-800 beats/min. The cerebrovascular CO2 response time and reactivity were evaluated during 5% CO2 exposure. During 1-4 s of ventricular pacing, mean arterial pressure (MAP) rapidly decreased, with minor changes in central venous and intracranial pressures. CBF was relatively well maintained in brain regions other than the MC (Ps ≤ 0.012) when moderate hypotension occurred (-34 mmHg ≤ ΔMAP ≤ -15 mmHg), whereas severe hypotension (-54 mmHg ≤ ΔMAP ≤ -35 mmHg) induced selective CBF distribution to regions other than the MC, thalamus, and dlPAG. The cerebrovascular CO2 response time/reactivity was rapid or high in the thalamus, dlPAG, and PB, which almost completely differed from the brain regions in which CBF was relatively maintained during pacing-induced severe hypotension. These results suggest that regional heterogeneity of CBF arises depending on the degree of tachyarrhythmia-induced hypotension. Clarifying the mechanisms and functions of CBF maintenance would be beneficial to syncope and cerebral ischemia management in patients with arrhythmia.

Harsh parenting, amygdala functional connectivity changes across childhood, and behavioral problems.

Harsh parenting in early childhood is related to offspring's adverse behavioral outcomes. Due to the scarcity of longitudinal neuroimaging data, few studies have explored the neurobiological underpinnings of this association, focusing on within-person variability. This study examined the temporal associations among harsh parenting, later behavioral problems, and the developmental trajectories of amygdala volume and amygdala resting-state functional connectivity (RSFC) profiles, using longitudinal neuroimaging data. The study was embedded in the Growing Up in Singapore Towards healthy Outcomes (GUSTO) cohort. T1-weighted (296 children, 642 scans) and resting-state functional scans (256 children, 509 scans) were collected at ages 4.5, 6, 7.5, and 10.5 years. Amygdala volume and RSFC between the amygdala and six brain regions that have leading roles in emotional regulation were extracted. Harsh parenting at 4.5 years and child behavioral problems at 10.5 years were assessed via parent-report questionnaires. Linear regression and linear mixed models were applied. Harsh parenting was associated with more severe externalizing problems in girls (β = 0.24, 95% CI 0.08-0.40) but not boys (pint = 0.07). In the overall sample, harsh parenting was associated with the developmental trajectories of amygdala-ACC, amygdala-OFC, and amygdala-DLPFC RSFC. In addition, the developmental trajectory of amygdala-ACC RSFC mediated the harsh parenting-externalizing problems association in girls (indirect effect = 0.06, 95% CI 0.01-0.14). Harsh parenting in early childhood was associated with amygdala neurocircuitry development and behavioral problems. The developmental trajectory of amygdala-ACC RSFC is a potential neural mechanism linking harsh parenting and externalizing problems in girls.

Integration across biophysical scales identifies molecular and cellular correlates of person-to-person variability in human brain connectivity

Brain connectivity arises from interactions across biophysical scales, ranging from molecular to cellular to anatomical to network level. To date, there has been little progress toward integrated analysis across these scales. To bridge this gap, from a unique cohort of 98 individuals, we collected antemortem neuroimaging and genetic data, as well as postmortem dendritic spine morphometric, proteomic and gene expression data from the superior frontal and inferior temporal gyri. Through the integration of the molecular and dendritic spine morphology data, we identified hundreds of proteins that explain interindividual differences in functional connectivity and structural covariation. These proteins are enriched for synaptic structures and functions, energy metabolism and RNA processing. By integrating data at the genetic, molecular, subcellular and tissue levels, we link specific biochemical changes at synapses to connectivity between brain regions. These results demonstrate the feasibility of integrating data from vastly different biophysical scales to provide a more comprehensive understanding of brain connectivity.

Neurocognitive correlates of cerebral mitochondrial function and energy metabolism using phosphorus magnetic resonance spectroscopy in older adults.

The goal of the current study was to learn about the role of cerebral mitochondrial function on cognition. Based on established cognitive neuroscience, clinical neuropsychology, and cognitive aging literature, we hypothesized mitochondrial function within a focal brain region would map onto cognitive behaviors linked to that brain region. To test this hypothesis, we used phosphorous (31P) magnetic resonance spectroscopy (MRS) to derive indirect markers of mitochondrial function and energy metabolism across two regions of the brain (bifrontal, left temporal). We administered cognitive tasks sensitive to frontal-executive or temporal-hippocampal systems to a sample of 70 cognitively unimpaired older adults with subjective memory complaints and a first-degree family history of Alzheimer's disease and predicted better executive function and recent memory performance would be related to greater frontal and temporal 31P MRS indirect markers, respectively. Results of separate hierarchical linear regressions indicated better recent memory scores were related to 31P MRS indirect markers of lower static energy and higher energy reserve within the left temporal voxel; these findings were associated with moderate effect sizes. Contrary to predictions, executive function performance was unrelated to 31P MRS indirect markers within the bilateral frontal voxel, which may reflect a combination of theoretical and/or methodological issues. Findings represent a snapshot of the relationship between cognition and 31P MRS indirect markers of mitochondrial function, providing potential avenues for future work investigating mitochondrial underpinnings of cognition. 31P MRS may provide a sensitive neuroimaging marker for differences in aspects of memory among persons at-risk for mild cognitive impairment or dementia.

Alterations of regional homogeneity and functional connectivity in different hoehn and yahr stages of Parkinson's disease

PurposeUsing regional homogeneity (ReHo) and functional connectivity (FC) to assess alterations in brain function and their potential relation to different Hoehn and Yahr (H&Y) stages in Parkinson's disease (PD). Materials and methods66 patients with PD and 57 age- and sex-matched healthy control (HC) participants were recruited. All subjects underwent clinical assessments and resting-state functional magnetic resonance imaging (rs-fMRI) scanning. We analyzed alterations in regional brain activity using ReHo analyses in all subjects and further explored their relationship to disease severity. Finally, the brain region significantly associated with disease severity was used as a seed point to analyze the FC changes between it and other brain regions in the whole brain. ResultsCompared with HC participants, PD patients showed a significant decrease ReHo in the sensorimotor network (bilateral precentral and postcentral gyrus). The ReHo value of the left precentral gyrus in PD patients decreased with increasing H&Y stage and correlated negatively with Unified Parkinson’s Disease Rating Scale (UPDRS) III scores. Further, FC analysis of the left precentral gyrus as a region of interest showed that functional activity between the left precentral gyrus and sensorimotor network, default network, and visual network was decreased. ConclusionThe left precentral gyrus plays an important role in the pathophysiological mechanisms of PD patients, and this finding further highlights the potential of the primary motor cortex (M1) as a non-invasive therapeutic target for neuromodulation in PD patients.

Effects of robot-assisted hand function therapy on brain functional mechanisms: a synchronized study using fNIRS and sEMG.

Robot-assisted hand function therapy is pivotal in the rehabilitation of patients with stroke; however, its therapeutic mechanism remains elusive. Currently, research examining the impact of robot-assisted hand function therapy on brain function in patients with stroke is scarce, and there is a lack of studies investigating the correlation between muscle activity and alterations in brain function. This study aimed to investigate the correlation between forearm muscle movement and brain functional activation by employing the synchronized use of functional near-infrared spectroscopy and surface electromyography methods. Moreover, it sought to compare neural activity patterns during different rehabilitation tasks and refine the mechanism of robot-assisted hand function therapy for post-stroke hand function impairments. Stroke patients with hand dysfunction underwent three sessions of robot-assisted hand function therapy within 2 weeks to 3 months of onset. The fNIRS-sEMG synchronous technique was used to observe brain function and forearm muscle activation. Ten participants were randomly assigned to receive mirror, resistance, or passive rehabilitation training. During the intervention, cortical and muscle activation information was obtained using fNIRS and electromyographic signals. The primary outcomes included changes in oxyhemoglobin concentration and root mean square of surface electromyography. Compared to the resting state, the Oxy-Hb concentration in the brain regions involved in three rehabilitation tasks with robot-assisted hand function therapy significantly increased (p < 0.05). Mirror therapy significantly enhanced the prefrontal cortex and the superior frontal cortex activation levels. In contrast, resistance therapy significantly promoted the activation of the supplementary motor area and the premotor cortex. Passive rehabilitation tasks showed some activation in the target brain area premotor cortex region. Robot-assisted hand function therapy has shown that forearm muscle movement is closely related to oxygenated hemoglobin concentration activity in specific brain regions during different rehabilitation tasks. The simultaneous sEMG-fNIRS study found a significant correlation between muscle movement and brain activity after stroke, which provides an important basis for understanding the treatment mechanism of hand function impairment.

Gamma frequency connectivity in frontostriatal networks associated with social preference is reduced with traumatic brain injury

Abstract Among the myriad of complications associated with traumatic brain injury (TBI), impairments in social behaviors and cognition have emerged as a significant area of concern. Animal models of social behavior are necessary to explore the underlying brain mechanisms contributing to chronic social impairments following brain injury. Here, we utilize large-scale brain recordings of local field potentials to identify neural signatures linked with social preference deficits following frontal brain injury. We used a controlled cortical impact model of TBI to create a severe bilateral injury centered on the prefrontal cortex. Behavior (social preference and locomotion) and brain activity (power and coherence) during a three-chamber social preference task were compared between sham and injured animals. Sham rats preferred to spend time with a social conspecific over an inanimate object. An analysis of local field oscillations showed that social preference was associated with a significant increase in coherence in gamma frequency band across widespread brain regions in these animals. Animals with a frontal TBI showed a significant reduction in this social preference, visiting an inanimate object more frequently and for more time. Reflecting these changes in social behavior, these animals also showed a significant reduction in gamma frequency (25–60 Hz) coherence associated with social preference.

Olfactory and trigeminal routes of HSV-1 CNS infection with regional microglial heterogeneity.

Herpes simplex virus type 1 (HSV-1) primarily targets the oral and nasal epithelia before establishing latency in the trigeminal ganglion (TG) and other peripheral ganglia. HSV-1 can also infect and become latent in the central nervous system (CNS) independent of latency in the TGs. Recent studies suggest entry to the CNS via two distinct routes: the TG-brainstem connection and olfactory nerve; however, to date, there is no characterization of brain regions targeted during HSV-1 primary infection. Furthermore, the immune response by microglia may also contribute to the heterogeneity between different brain regions. However, the response to HSV-1 by microglia has not been characterized in a region-specific manner. This study investigated the time course of HSV-1 spread within the olfactory epithelium (OE) and CNS following intranasal inoculation and the corresponding macrophage/microglial response in a C57BL/6 mouse model. We found an apical to basal spread of HSV-1 within the OE and underlying tissue accompanied by an inflammatory response of macrophages. OE infection was followed by infection of a small subset of brain regions targeted by the TG in the brainstem and other cranial nerve nuclei, including the vagus and hypoglossal nerve. Furthermore, other brain regions were positive for HSV-1 antigens, such as the locus coeruleus (LC), raphe nucleus (RaN), and hypothalamus while sparing the hippocampus and cortex. Within each brain region, microglia activation also varied widely. These findings provide critical insights into the region-specific dissemination of HSV-1 within the CNS, elucidating potential mechanisms linking viral infection to neurological and neurodegenerative diseases.IMPORTANCEThis study shows how herpes simplex virus type 1 (HSV-1) spreads within the brain after infecting the nasal passages. Our data reveal the distinct pattern of HSV-1 through the brain during a non-encephalitic infection. Furthermore, microglial activation was also temporally and spatially specific, with some regions of the brain having sustained microglial activation even in the absence of viral antigens. Previous reports have identified specific brain regions found to be positive for HSV-1 infection; however, to date, there has not been a concise investigation of the anatomical spread of HSV-1 and the brain regions consistently vulnerable to viral entry and spread. Understanding these region-specific differences in infection and immune response is crucial because it links HSV-1 infection to potential triggers for neurological and neurodegenerative diseases.

Hemodynamic cortical ripples through cyclicity analysis

Abstract A fine-grained understanding of dynamics in cortical networks is crucial to unpacking brain function. Resting-state functional magnetic resonance imaging (fMRI) gives rise to time series recordings of the activity of different brain regions, which are aperiodic and lack a base frequency. Cyclicity analysis, a novel technique robust under time reparametrizations, is effective in recovering the temporal ordering of such time series, collectively considered components of a multidimensional trajectory. Here, we extend this analytical method for characterizing the dynamic interaction between distant brain regions and apply it to the data from the Human Connectome Project. Our analysis detected cortical traveling waves of activity propagating along a spatial axis, resembling cortical hierarchical organization with consistent lead-lag relationships between specific brain regions in resting-state scans. In fMRI scans involving tasks, we observed short bursts of task-modulated strong temporal ordering that dominate overall lead-lag relationships between pairs of regions in the brain that align temporally with stimuli from the tasks. Our results suggest a possible role played by waves of excitation sweeping through brain regions that underlie emergent cognitive functions.

Abnormal Granger causal connectivity based on altered gray matter volume and associated neurotransmitters of adolescents with internet gaming disorder revealed by a multimodal neuroimaging study

Although prior studies have revealed alterations in gray matter volume (GMV) among individuals with internet gaming disorder (IGD). The brain's multifaceted functions hinge crucially on the intricate connections and communication among distinct regions. However, the intricate interaction of information between brain regions with altered GMV and other regions, and how they synchronize with various neurotransmitter systems, remains enigmatic. Therefore, we aimed to integrate structural, functional and molecular data to explore the GMV-based Granger causal connectivity abnormalities and their correlated neurotransmitter systems in IGD adolescents. Voxel-based morphometry (VBM) analysis was firstly performed to investigate GMV differences between 37 IGD adolescents and 35 matched controls. Brain regions with altered GMV were selected as seeds for further Granger causality analysis (GCA). Two-sample t tests were performed using the SPM12 toolkit to compare the GMV and Granger causal connectivity between IGD and control groups (GRF corrected, Pvoxel<0.005, Pcluster<0.05). Then, GMV-based Granger causal connectivity was spatially correlated with PET- and SPECT-derived maps covering multifarious neurotransmitter systems. Multiple comparison correction was performed using false discovery rate (FDR). Compared with controls, IGD adolescents showed higher GMV in the caudate nucleus and lingual gyrus. For the GCA, IGD adolescents showed higher Granger causal connectivity from insula, putamen, supplementary motor area (SMA) and middle cingulum cortex (MCC) to the caudate nucleus, and lower Granger causal connectivity from superior/inferior parietal gyrus (SPG/IPG) and middle occipital gyrus (MOG) to the lingual gyrus. Besides, GMV-based Granger causal connectivity of IGD adolescents were associated with the dopaminergic, serotonergic, GABAergic and noradrenaline systems. This study revealed that the caudate nucleus and lingual gyrus may be the key sites of neuroanatomical changes in IGD adolescents, and whole-brain Granger causal connectivity abnormalities based on altered GMV involved large brain networks including reward, cognitive control, and visual attention networks, and these abnormalities are associated with a variety of neurotransmitter systems, which may be associated with higher reward sensitivity, cognitive control, and attention control dysfunction.

Transcranial Focused Ultrasound Neuromodulation in Psychiatry: Main Characteristics, Current Evidence, and Future Directions

Non-invasive brain stimulation (NIBS) techniques are designed to precisely and selectively target specific brain regions, thus enabling focused modulation of neural activity. Among NIBS technologies, low-intensity transcranial focused ultrasound (tFUS) has emerged as a promising new modality. The application of tFUS can safely and non-invasively stimulate deep brain structures with millimetric precision, offering distinct advantages in terms of accessibility to non-cortical regions over other NIBS methods. However, to date, several tFUS aspects still need to be characterized; furthermore, there are only a handful of studies that have utilized tFUS in psychiatric populations. This narrative review provides an up-to-date overview of key aspects of this NIBS technique, including the main components of a tFUS system, the neuronavigational tools used to precisely target deep brain regions, the simulations utilized to optimize the stimulation parameters and delivery of tFUS, and the experimental protocols employed to evaluate the efficacy of tFUS in psychiatric disorders. The main findings from studies in psychiatric populations are presented and discussed, and future directions are highlighted.

Maternal separation alters peripheral immune responses associated with IFN-γ and OT in mice

The co-evolution of social behavior and the immune system plays a critical role in individuals' adaptation to their environment. However, also need for further research on the key molecules that co-regulate social behavior and immunity. This study focused on neonatal mice that were separated from their mothers for 4 hours per day between the 6th and 16th day after birth. The results showed that these mice had lower plasma levels of IFN-γ and oxytocin, but higher levels of plasma glucocorticoids (GC), then impacting their social abilities. Additionally, maternal separation led to decreased levels of BDNF, IGF2, and CREB mRNAs in the hippocampus, while levels in the prefrontal cortex (PFC) remained unaffected. Maternal separation also resulted in increased levels of oxytocin and CRH mRNA in the hypothalamus, as well as an increase in CD45+ lymphocyte subsets in the meninges and choroid plexus (CP), with CD8+ lymphocytes in meninges and CD4+ lymphocytes in CP showing an increase. In IFN-γ-/- mice, a decrease in social preference was observed alongside lower plasma oxytocin levels. Moreover, IFN-γ-/- mice exhibited reduced numbers of oxytocin neurons in the paraventricular nucleus of the paraventricular nucleus of hypothalamus (PVN), decreased BDNF levels in the PFC and hippocampus, and alterations in CD45+ lymphocytes in CP and meninges, with an increase in CD8+ lymphocytes in meninges and CD4+ lymphocytes in CP. These findings highlight the immunological impact of social stress on IFN-γ regulation, suggesting that the immunomodulatory molecule IFN-γ may influence social behavior by affecting synaptic efficiency in brain regions such as the hippocampus and PFC, which are linked to oxytocin in the PVN.

Decrease in walking ability with increased functional connectivity between multiple brain areas in Parkinson's disease: a functional near-infrared spectroscopy study.

Gait disturbances significantly impact the mobility and quality of life of individuals with Parkinson's disease (PD). This study aims to delve into the cortical mechanisms underlying gait disorders in PD, specifically focusing on the prefrontal cortex (PFC), premotor cortex (PMC), and primary somatosensory cortex (PSC). To compare the functional connectivity of the PFC, PMC, and PSC regions during walking between individuals with PD and healthy controls. The study included 30 individuals with PD (mean age 62.40 ± 7.16 years) and 22 healthy older adults (mean age 60.95 ± 6.34 years). All participants were requested to walk back and forth at a comfortable pace for 30 s over a 10-meter course three times. A mobile functional near-infrared spectroscopy (fNIRS) system was employed to evaluate the oxyhemoglobin concentration change (∆HbO2). To assess the interactions between the PFC, PMC, and PSC, the connectivity strength between different fNIRS channels was computed. Individuals with PD in the off-state exhibited significantly decreased walking speed and shorter stride length compared to the healthy controls. For six brain regions including the left (L) and right (R) PFC, PMC, and PSC, no significant differences in functional connectivity within each region were found between the PD and control groups. However, when it comes to the functional connectivity between every two regions, the PD group exhibited stronger functional connectivity than the control group in the LPFC-LPMC, LPFC-RPMC, LPFC-LPSC, RPFC-LPMC, RPFC-LPSC, LPMC-LPSC, LPMC-RPSC, and RPMC-RPSC. Positive correlations were found between gait performance (speed and stride length) and functional connectivity within the RPMC as well as between the RPMC and the RPSC. Individuals with PD exhibit notable gait disturbances and increased functional connectivity in brain regions responsible for sensorimotor integration and motor function in their off-state. Strengthening the functional connectivity within the RPMC and between the RPMC and the RPSC could be a potential target for future treatments of gait impairments in PD.

A Relationship of Monoamine Oxidase-A with Serotonin in Violent Antisocial Behavior in Iraqi Prisoners

It is thought that the monoamine oxidase-A (MAOA) enzyme, which catalyzes key brain signaling chemicals like serotonin, noradrenaline, and dopamine, indirectly influences antisocial behavior by disrupting the neurotransmitter balance in brain regions and neural networks. This study aims to assess the MAOA enzyme level in serum and serotonin linked to antisocial behavior in cases in the prison of Baghdad City, Iraq. Blood samples were collected from (63) prisoners and (27) control groups, ages 18 years to 65 years, with a mean ± SD of 37.8 ± 8.8, all males, with different prison terms and different crimes for prisoners in the prison at Baghdad City, Iraq. MAOA and serotonin levels were measured in serum in prisoners and healthy men, and the results showed the serum levels of MAOA enzyme and serotonin were decreased in prisoners compared to the healthy (11.5 IU/ml vs. 19.5 IU/ml) and (79 IU/ml vs. 439 IU/ml), respectively, with the observed difference being significant (P &lt; 0.001(. The results of the relationship between education and social violence were: illiterate 11.1%, primary school 27%, secondary 52.4%, and university 9.5%. The median serum level of MAOA and serotonin in the age group 18–39 years was (11.3 IU/ml, 68.3 ng/ml), respectively, and in the age group 40–65 years was (13 IU/ml, 139 ng/ml), respectively.

The causal relationship of DTI phenotypes and epilepsy: A two sample mendelian randomization study.

Clinical studies indicated a link between DTI imaging characteristics and epilepsy, but the causality of this connection had not been established. Therefore, we employed the Mendelian randomization analysis method to determine the causal relationship between DTI imaging characteristics and epilepsy. We used Mendelian randomization analysis to identify the causal relationship between brain structure and the risk of epilepsy. GWAS data of DTI phenotypes, focal epilepsy, and genetic generalized epilepsy (GGE) were utilized in the analysis. Our study found that DTI imaging phenotypes had a causal risk relationship with epilepsy. These phenotypes had a statistical impact on the risk of epilepsy seizures. There were differences in DTI phenotype causality between GGE and focal epilepsy, which were associated with the clinical phenotype differences of the two types of epilepsy. Our study demonstrated that the diagnosis of subtypes could be assisted by comparing the differences in DTI phenotypes of specific brain regions. This meant that by studying the changes in brain regions before the onset of epilepsy, we might be able to intervene in epilepsy at an earlier stage. Our study used Mendelian randomization to explore the causal relationship between brain structure, as seen in DTI imaging, and epilepsy. We found that specific DTI phenotypes are linked to an increased risk of epilepsy seizures, with notable differences between genetic generalized epilepsy and focal epilepsy. This suggested that analyzing DTI phenotypes could help in diagnosing and potentially intervening in epilepsy earlier by finding brain changes before seizures begin.

Behavioral and psychological symptoms and brain volumes in community-dwelling older persons from the Nakayama Study

The frequency of behavioral and psychological symptoms of dementia (BPSD) is high, and it is a challenge to elucidate its neural substrates underlying their development. In recent years, many findings have been reported on the relationship between BPSD and brain volume in dementia patients. However, the results are not fully conclusive. Furthermore, there have been few population-based studies. Therefore, the relationship between BPSD and brain volume was investigated as an exploratory study. Of the 927 older persons who participated in the fifth Nakayama study, 90 were included in this analysis, consisting of 52 patients with mild cognitive impairment and 38 patients with dementia, with head MRI and the Neuropsychiatric Inventory (NPI) data. Multiple regression analysis was used to examine the association between the total score of each BPSD score on the NPI and brain volume estimated by FreeSurfer. On multivariate adjustment, even after false discovery rate correction, insular cortical volumes decreased significantly as total scores for apathy/indifference increased (p value = 0.002, q-value = 0.01). Similarly, total brain volume decreased significantly as total scores for appetite and eating disturbance increased (p value = 0.03), and parietal, temporal, and hippocampal cortical volumes also decreased significantly as total scores for appetite and eating disturbance increased (all p and q values < 0.05). This study’s results suggest that apathy is negatively correlated with insular cortical volume, and that appetite and eating disturbance are also correlated with brain regions, including parietal, temporal, and hippocampal volume in a community-dwelling older population.