Brain Structural Features Research Articles

The correlation between brain structure characteristics and emotion regulation ability in children at high risk of autism spectrum disorder.

As indicated by longitudinal observation, autism has difficulty controlling emotions to a certain extent in early childhood, and most children's emotional and behavioral problems are further aggravated with the growth of age. This study aimed at exploring the correlation between white matter and white matter fiber bundle connectivity characteristics and their emotional regulation ability in children with autism using machine learning methods, which can lay an empirical basis for early clinical intervention of autism. Fifty-five high risk of autism spectrum disorder (HR-ASD) children and 52 typical development (TD) children were selected to complete the skull 3D-T1 structure and diffusion tensor imaging (DTI). The emotional regulation ability of the two groups was compared using the still-face paradigm (SFP). The classification and regression models of white matter characteristics and white matter fiber bundle connections of emotion regulation ability in the HR-ASD group were built based on the machine learning method. The volume of the right amygdala (R2 = 0.245) and the volume of the right hippocampus (R2 = 0.197) affected constructive emotion regulation strategies. FA (R2 = 0.32) and MD (R2 = 0.34) had the predictive effect on self-stimulating behaviour. White matter fiber bundle connection predicted constructive regulation strategies (positive edging R2 = 0.333, negative edging R2 = 0.334) and mother-seeking behaviors (positive edging R2 = 0.667, negative edging R2 = 0.363). The emotional regulation ability of HR-ASD children is significantly correlated with the connections of multiple white matter fiber bundles, which is a potential neuro-biomarker of emotional regulation ability.

The role of perfusion, grey matter volume and behavioural phenotypes in the data-driven classification of cognitive syndromes

BackgroundThe use of structural and perfusion brain imaging in combination with behavioural information in the prediction of cognitive syndromes using a data-driven approach remains to be explored. Here, we thus examined the contribution of brain structural and perfusion imaging and behavioural features to the existing classification of cognitive syndromes using a data-driven approach.MethodsStudy participants belonged to the community-based Biomarker and Cognition Cohort Study in Singapore who underwent neuropsychological assessments, structural-functional MRI and blood biomarkers. Participants had a diagnosis of cognitively normal (CN), subjective cognitive impairment (SCI), mild cognitive impairment (MCI) and dementia. Cross-sectional structural and cerebral perfusion imaging, behavioural scale data including mild behaviour impairment checklist, Pittsburgh Sleep Quality Index and Depression, Anxiety and Stress scale data were obtained.ResultsThree hundred seventy-three participants (mean age 60.7 years; 56% female sex) with complete data were included. Principal component analyses demonstrated that no single modality was informative for the classification of cognitive syndromes. However, multivariate glmnet analyses revealed a specific combination of frontal perfusion and temporo-frontal grey matter volume were key protective factors while the severity of mild behaviour impairment interest sub-domain and poor sleep quality were key at-risk factors contributing to the classification of CN, SCI, MCI and dementia (p < 0.0001). Moreover, the glmnet model showed best classification accuracy in differentiating between CN and MCI cognitive syndromes (AUC = 0.704; sensitivity = 0.698; specificity = 0.637).ConclusionsBrain structure, perfusion and behavioural features are important in the classification of cognitive syndromes and should be incorporated by clinicians and researchers. These findings illustrate the value of using multimodal data when examining syndrome severity and provide new insights into how cerebral perfusion and behavioural impairment influence classification of cognitive syndromes.

Large-scale investigation of white matter structural differences in bilingual and monolingual children: An adolescent brain cognitive development data study.

Emerging research has provided valuable insights into the structural characteristics of the bilingual brain from studies of bilingual adults; however, there is a dearth of evidence examining brain structural alterations in childhood associated with the bilingual experience. This study examined the associations between bilingualism and white matter organization in bilingual children compared to monolingual peers leveraging the large-scale data from the Adolescent Brain Cognitive Development (ABCD) Study. Then, 446 bilingual children (ages 9-10) were identified from the participants in the ABCD data and rigorously matched to a group of 446 monolingual peers. Multiple regression models for selected language and cognitive control white matter pathways were used to compare white matter fractional anisotropy (FA) values between bilinguals and monolinguals, controlling for demographic and environmental factors as covariates in the models. Results revealed significantly lower FA values in bilinguals compared to monolinguals across established dorsal and ventral language network pathways bilaterally (i.e., the superior longitudinal fasciculus and inferior frontal-occipital fasciculus) and right-hemispheric pathways in areas related to cognitive control and short-term memory (i.e., cingulum and parahippocampal cingulum). In contrast to the enhanced FA values observed in adult bilinguals relative to monolinguals, our findings of lower FA in bilingual children relative to monolinguals may suggest a protracted development of white matter pathways associated with language and cognitive control resulting from dual language learning in childhood. Further, these findings underscore the need for large-scale longitudinal investigation of white matter development in bilingual children to understand neuroplasticity associated with the bilingual experience during this period of heightened language learning.

Multimodal neuroimaging correlates of physical-cognitive covariation in Chilean adolescents. The Cogni-Action Project

Health-related behaviours have been related to brain structural features. In developing settings, such as Latin America, high social inequality has been inversely associated with several health-related behaviours affecting brain development. Understanding the relationship between health behaviours and brain structure in such settings is particularly important during adolescence when critical habits are acquired and ingrained. In this cross-sectional study, we carry out a multimodal analysis identifying a brain region associated with health-related behaviours (i.e., adiposity, fitness, sleep problems and others) and cognitive/academic performance, independent of socioeconomic status in a large sample of Chilean adolescents. Our findings suggest that the relationship between health behaviours and cognitive/academic performance involves a particular brain phenotype that could play a mediator role. These findings fill a significant gap in the literature, which has largely focused on developed countries and raise the possibility of promoting healthy behaviours in adolescence as a means to influence brain structure and thereby cognitive/academic achievement, independently of socioeconomic factors. By highlighting the potential impact on brain structure and cognitive/academic achievement, policymakers could design interventions that are more effective in reducing health disparities in developing countries.

基于脑结构特征和认知行为特征的阿尔茨海默症分类诊断

基于脑结构特征和认知行为特征的阿尔茨海默症分类诊断

Neuromorphometric associations with mood, cognition, and self-reported exercise levels in epilepsy and healthy individuals

Regular physical activity may promote beneficial neuroplasticity, e.g., increased hippocampus volume. However, it is unclear whether self-reported physical exercise in leisure (PEL) levels are associated with the brain structure features demonstrated by exercise interventions. This pilot study investigated the relationship between PEL, mood, cognition, and neuromorphometry in patients with idiopathic generalized epilepsy (IGEs) compared to healthy controls (HCs). Seventeen IGEs and 19 age- and sex-matched HCs underwent magnetic resonance imaging (MRI) at 3T. The Baecke Questionnaire of Habitual Physical Activity, Profile of Mood States, and Montreal Cognitive Assessment (MoCA) assessed PEL, mood, and cognition, respectively. Structural MRI data were analyzed by voxel- and surface-based morphometry. IGEs had significantly lower PEL (p < 0.001), poorer mood (p = 0.029), and lower MoCA scores (p = 0.027) than HCs. These group differences were associated with reduced volume, decreased gyrification, and altered surface topology (IGEs < HCs) in frontal, temporal and cerebellar regions involved in executive function, memory retrieval, and emotional regulation, respectively.These preliminary results support the notion that increased PEL may promote neuroplasticity in IGEs, thus emphasizing the role of physical activity in promoting brain health in people with epilepsy.

Changes in microstructural similarity of hippocampal subfield circuits in pathological cognitive aging.

The hippocampal networks support multiple cognitive functions and may have biological roles and functions in pathological cognitive aging (PCA) and its associated diseases, which have not been explored. In the current study, a total of 116 older adults with 39 normal controls (NC) (mean age: 52.3 ± 13.64years; 16 females), 39 mild cognitive impairment (MCI) (mean age: 68.15 ± 9.28years, 14 females), and 38 dementia (mean age: 73.82 ± 8.06years, 8 females) were included. The within-hippocampal subfields and the cortico-hippocampal circuits were assessed via a micro-structural similarity network approach using T1w/T2w ratio and regional gray matter tissue probability maps, respectively. An analysis of covariance was conducted to identify between-group differences in structural similarities among hippocampal subfields. The partial correlation analyses were performed to associate changes in micro-structural similarities with cognitive performance in the three groups, controlling the effect of age, sex, education, and cerebralsmall-vesseldisease. Compared with the NC, an altered T1w/T2w ratio similarity between left CA3 and left subiculum was observed in the mild cognitive impairment (MCI) and dementia. The left CA3 was the most impaired region correlated with deteriorated cognitive performance. Using these regions as seeds for GM similarity comparisons between hippocampal subfields and cortical regions, group differences were observed primarily between the left subiculum and several cortical regions. By utilizing T1w/T2w ratio as a proxy measure for myelin content, our data suggest that the imbalanced synaptic weights within hippocampal CA3 provide a substrate to explain the abnormal firing characteristics of hippocampal neurons in PCA. Furthermore, our work depicts specific brain structural characteristics of normal and pathological cognitive aging and suggests a potential mechanism for cognitive aging heterogeneity.

Recalibrating single-study effect sizes using hierarchical Bayesian models.

There are growing concerns about commonly inflated effect sizes in small neuroimaging studies, yet no study has addressed recalibrating effect size estimates for small samples. To tackle this issue, we propose a hierarchical Bayesian model to adjust the magnitude of single-study effect sizes while incorporating a tailored estimation of sampling variance. We estimated the effect sizes of case-control differences on brain structural features between individuals who were dependent on alcohol, nicotine, cocaine, methamphetamine, or cannabis and non-dependent participants for 21 individual studies (Total cases: 903; Total controls: 996). Then, the study-specific effect sizes were modeled using a hierarchical Bayesian approach in which the parameters of the study-specific effect size distributions were sampled from a higher-order overarching distribution. The posterior distribution of the overarching and study-specific parameters was approximated using the Gibbs sampling method. The results showed shrinkage of the posterior distribution of the study-specific estimates toward the overarching estimates given the original effect sizes observed in individual studies. Differences between the original effect sizes (i.e., Cohen's d) and the point estimate of the posterior distribution ranged from 0 to 0.97. The magnitude of adjustment was negatively correlated with the sample size (r = -0.27, p < 0.001) and positively correlated with empirically estimated sampling variance (r = 0.40, p < 0.001), suggesting studies with smaller samples and larger sampling variance tended to have greater adjustments. Our findings demonstrate the utility of the hierarchical Bayesian model in recalibrating single-study effect sizes using information from similar studies. This suggests that Bayesian utilization of existing knowledge can be an effective alternative approach to improve the effect size estimation in individual studies, particularly for those with smaller samples.

Multi-modal neuroimaging signatures predict cognitive decline in multiple sclerosis: A 5-year longitudinal study

BackgroundCognitive impairment is a hallmark of multiple sclerosis (MS) but is usually an under-recorded symptom of disease progression. Identifying the predictive signatures of cognitive decline in people with MS (pwMS) over time is important to ensure effective preventative treatment strategies. Structural and functional brain characteristics as measured by various magnetic resonance (MR) methods have been correlated with variation in cognitive function in MS, but typically these studies are limited to a single MR modality and/or are cross-sectional designs. Here we assess the predictive value of multiple different MR modalities in relation to cognitive decline in pwMS over 5 years. MethodsA cohort of 43 pwMS was assessed at baseline and 5 years follow-up. Baseline (input) data consisted of 70 multi-modal MRI measures for different brain regions including magnetic resonance spectroscopy (MRS), diffusion tensor imaging (DTI) and standard volumetrics. Age, sex, disease duration and treatment were included as clinical inputs. Cognitive function was assessed using the Audio Recorded Cognitive Screen (ARCS) and the Symbol Digit Modalities Test (SDMT). Prediction modelling was performed using the machine learning package - GLMnet, where a penalised regression was applied to identify multi-modal signatures with the most predictive value (and the least error) for each outcome. ResultsThe multi-modal approach to neuroimaging was able to accurately predict cognitive decline in pwMS. The best performing model for change in total ARCS (tARCS) included 16 features from across the various MR modalities and explained 54 % of the variation in change over time (R2=0.54, 95 % CI=0.48–0.51). The features included nine MRS, four volumetric and two DTI parameters. The model also selected disease duration, but not treatment, as a predictive feature. By comparison, the best model for SDMT included several of the same above features and explained 39 % of the change over time (R2=0.39, 95 % CI=0.48–0.51). Conventional volumetric measures were about half as good at predicting change in tARCS score compared to the best multi-modal model (R2=0.26 95 % CI:0.22–0.29). The clinical interpretation of the best predictive model for change in tARCS showed that cognitive decline could be predicted with >90 % accuracy in this cohort (AUC=0.92, SE=0.86 - 0.94). ConclusionMulti-modal MRI signatures can predict cognitive decline in a cohort of pwMS over 5 years with high accuracy. Future studies will benefit from the inclusion of even more MR modalities e.g., functional MRI, quantitative susceptibility mapping, magnetisation transfer imaging, as well as other potential predictors e.g., genetic and environmental factors. With further validation, this signature could be used in future trials with high-risk patients to personalise the management of cognitive decline in pwMS, even in the absence of relapses.

Early life factors and individual differences in the brain through the human lifespan – association of intercept or change?

AbstractBackgroundHuman fetal development has been associated with brain health at later stages. In this presentation, I review results of analyses by the center for Lifespan Changes in Brain and cognition (LCBC), on whether and how consistently factors present in utero, including genetics (APOE4; polygenic risk for Alzheimer´s Disease; AD), prenatal drug exposure and, especially, growth in utero, as indexed by birth weight (BW), relates to lifespan brain characteristics and changes.MethodWe investigated associations between BW and cortical surface area, thickness and volume as derived from MRIs, across and within developmental, aging and lifespan longitudinal samples (N = 5794, 4‐82 years of age, w/ 386 monozygotic (MZ) twins, followed for up to 8.3 years w/12,088 brain MRIs).ResultsAssociations of BW and structural brain characteristics appear to be identifiable through the lifespan, with largely topographically consistent effects across samples of varying age. In developmental (ABCD), older adult and aging (UKB) and lifespan (LCBC) longitudinal samples, positive associations between BW and cortical surface area and volume were remarkably stable within and across samples of different age and origin, with spatial correlations in the range r = .51‐.79. In contrast, there was modest and no consistent effect of BW on brain changes. Effects of BW discordance in the twin subsample indicated the effects were partly environmental. This stable effect of an early life factor (BW), is similar to effects through the lifespan of genetic risk for AD, and persistent effects of prenatal opioid and ‐polydrug exposure in childhood and young adulthood.ConclusionThe influence of these early life factors, as here shown for BW, on brain topography, appear in part stable through the lifespan, being reliably seen in development, adulthood, and aging, as an intercept effect. These findings support early life influence on the brain through the lifespan according to a threshold model of brain reserve, rather than a maintenance model. To test experimentally whether early life factors may still influence slopes of brain and cognitive change, a navigation training neuroimaging study of twins with known extent of discordance in BW has been conducted, preliminary data from which is also presented.

Physiological Correlates of Hypnotizability: Hypnotic Behaviour and Prognostic Role in Medicine.

Studies in the field of experimental hypnosis highlighted the role of hypnotizability in the physiological variability of the general population. It is associated, in fact, with a few differences which are observable in the ordinary state of consciousness and in the absence of suggestions. The aim of the present scoping review is summarizing them and indicate their relevance to the neural mechanisms of hypnosis and to the prognosis and treatment of a few medical conditions. Individuals with high, medium and low hypnotizability scores display different cerebral functional differences-i.e., functional equivalence between imagery and perception/action, excitability of the motor cortex, interoceptive accuracy-possibly related to brain structural and functional characteristics, and different control of blood supply at peripheral and cerebral level, likely due to different availability of endothelial nitric oxide. These differences are reviewed to support the idea of their participation in hypnotic behaviour and to indicate their prognostic and therapeutic usefulness in a few medical conditions.

Structural brain feature is associated with changes of masticatory performance in healthy elderly people: Evidence from longitudinal neuroimaging research over two years.

Human neuroimaging studies have revealed the association between brain structure and masticatory function. However, the majority of the studies adopted a cross-sectional design, which hardly reveals the change in masticatory function and brain structure between different timepoints, and the dynamical association between changes in masticatory function and changes in brain structure has not been elucidated. With a longitudinal design, we assessed the association between changes in masticatory performance (MP) and regional brain volume. Twenty-two elderly participants received assessments of the number of missing teeth and MP (via colour-changeable chewing gum) when they entered the study (i.e. the initial stage, T0 ), approximately 6 months later (T0.5 ), and approximately 1-2 years later (T1 ). Difficulty of food intake was assessed using a questionnaire. The participants received magnetic resonance imaging (MRI) at T0 and T1 . The brain volume of the motor-related area was estimated using FreeSurfer for MRI data. The associations between different stages were analysed using Spearman's rho correlation coefficients. (1) Individually, a smaller volume of right primary motor cortex at T0 was associated with increased MP from T0 to T1 , suggesting the brain's role in changing oral functions; (2) higher MP at T0 was associated with an increased volume of the left superior frontal cortex from T0 to T1 p, suggesting a potential effect on brain plasticity, and (3) increased difficulty to eat was associated with decrease MP but not brain volume of motor-related area. The preliminary findings revealed a complicated pattern of structural brain features and masticatory function in elderly people, and either the hypothesis that the brain predisposes masticatory function or the hypothesis that mastication reshapes the brain is oversimplified.

Altered brain functional networks in schizophrenia with persistent negative symptoms: an activation likelihood estimation meta-analysis

ObjectiveTo investigate brain structural and functional characteristics of three brain functional networks including default mode network (DMN), central executive network (CEN), and salience network (SN) in persistent negative symptoms (PNS) patients.MethodsWe performed an activation likelihood estimation (ALE) meta-analysis of functional connectivity (FC) studies and voxel-based morphometry (VBM) studies to detect specific structural and functional alterations of brain networks between PNS patients and healthy controls.ResultsSeventeen VBM studies and twenty FC studies were included. In the DMN, PNS patients showed decreased gray matter in the bilateral medial frontal gyrus and left anterior cingulate gyrus and a significant reduction of FC in the right precuneus. Also, PNS patients had a decrease of gray matter in the left inferior parietal lobules and medial frontal gyrus, and a significant reduction of FC in the bilateral superior frontal gyrus in the CEN. In comparison with healthy controls, PNS patients exhibited reduced gray matter in the bilateral insula, anterior cingulate gyrus, left precentral gyrus and right claustrum and lower FC in these brain areas in the SN, including the left insula, claustrum, inferior frontal gyrus and extra-nuclear.ConclusionThis meta-analysis reveals brain structural and functional imaging alterations in the three networks and the interaction among these networks in PNS patients, which provides neuroscientific evidence for more personalized treatment.Systematic Review RegistrationThe PROSPERO (https://www.crd.york.ac.uk/PROSPERO/, registration number: CRD42022335962).

Artificial-intelligence-based MRI brain volumetry in patients with essential tremor and tremor-dominant Parkinson's disease.

Essential tremor and Parkinson's disease patients may present with various tremor types. Overlapping tremor features can be challenging to diagnosis and misdiagnosis is common. Although underlying neurodegenerative mechanisms are suggested, neuroimaging studies arrived at controversial results and often the different tremor types were not considered. We investigated whether different tremor types displayed distinct structural brain features. Structural MRI of 61 patients with essential tremor and 29 with tremor-dominant Parkinson's disease was analysed using a fully automated artificial-intelligence-based brain volumetry to compare volumes of several cortical and subcortical regions. Furthermore, essential tremor subgroups with and without rest tremor or more pronounced postural and kinetic tremor were investigated. Deviations from an internal reference collective of age- and sex-adjusted healthy controls and volumetric differences between groups were examined; regression analysis was used to determine the contribution of disease-related factors on volumetric measurements. Compared with healthy controls, essential tremor and tremor-dominant Parkinson's disease patients displayed deviations in the occipital lobes, hippocampus, putamen, pallidum and mesencephalon while essential tremor patients exhibited decreased volumes within the nucleus caudatus and thalamus. Analysis of covariance revealed similar volumetric patterns in both diseases. Essential tremor patients without rest tremor showed a significant atrophy within the thalamus compared to tremor-dominant Parkinson's disease and atrophy of the mesencephalon and putamen were found in both subgroups compared to essential tremor with rest tremor. Disease-related factors contribute to volumes of occipital lobes in both diseases and to volumes of temporal lobes in essential tremor and the putamen in Parkinson's disease. Fully automated artificial-intelligence-based volumetry provides a fast and rater-independent method to investigate brain volumes in different neurological disorders and allows comparisons with an internal reference collective. Our results indicate that essential tremor and tremor-dominant Parkinson's disease share structural changes, indicative of neurodegenerative mechanisms, particularly of the basal-ganglia-thalamocortical circuitry. A discriminating, possibly disease-specific involvement of the thalamus was found in essential tremor patients without rest tremor and the mesencephalon and putamen in tremor-dominant Parkinson's disease and essential tremor without rest tremor.

Neuroanatomical correlates of aggressiveness: a case-control voxel- and surface-based morphometric study.

Aggression occurs across the population ranging on a symptom continuum. Most previous studies have used magnetic resonance imaging in clinical/forensic samples, which is associated with several confounding factors. The present study examined structural brain characteristics in two healthy samples differing only in their propensity for aggressive behavior. Voxel- and surface-based morphometry (SBM) analyses were performed on 29 male martial artists and 32 age-matched male controls. Martial artists had significantly increased mean gray matter volume in two frontal (left superior frontal gyrus and bilateral anterior cingulate cortex) and one parietal (bilateral posterior cingulate gyrus and precuneus) brain clusters compared to controls (whole brain: p < 0.001, cluster level: family-wise error (FWE)-corrected). SBM analyses revealed a trend for greater gyrification indices in martial artists compared to controls in the left lateral orbital frontal cortex and the left pars orbitalis (whole brain: p < 0.001, cluster level: FWE-corrected). The results indicate brain structural differences between martial artists and controls in frontal and parietal brain areas critical for emotion processing/inhibition of emotions as well as empathic processes. The present study highlights the importance of studying healthy subjects with a propensity for aggressive behavior in future structural MRI research on aggression.

Transdiagnostic subgroups of cognitive impairment in early affective and psychotic illness

Cognitively impaired and spared patient subgroups were identified in psychosis and depression, and in clinical high-risk for psychosis (CHR). Studies suggest differences in underlying brain structural and functional characteristics. It is unclear whether cognitive subgroups are transdiagnostic phenomena in early stages of psychotic and affective disorder which can be validated on the neural level. Patients with recent-onset psychosis (ROP; N = 140; female = 54), recent-onset depression (ROD; N = 130; female = 73), CHR (N = 128; female = 61) and healthy controls (HC; N = 270; female = 165) were recruited through the multi-site study PRONIA. The transdiagnostic sample and individual study groups were clustered into subgroups based on their performance in eight cognitive domains and characterized by gray matter volume (sMRI) and resting-state functional connectivity (rsFC) using support vector machine (SVM) classification. We identified an impaired subgroup (NROP = 79, NROD = 30, NCHR = 37) showing cognitive impairment in executive functioning, working memory, processing speed and verbal learning (all p < 0.001). A spared subgroup (NROP = 61, NROD = 100, NCHR = 91) performed comparable to HC. Single-disease subgroups indicated that cognitive impairment is stronger pronounced in impaired ROP compared to impaired ROD and CHR. Subgroups in ROP and ROD showed specific symptom- and functioning-patterns. rsFC showed superior accuracy compared to sMRI in differentiating transdiagnostic subgroups from HC (BACimpaired = 58.5%; BACspared = 61.7%, both: p < 0.01). Cognitive findings were validated in the PRONIA replication sample (N = 409). Individual cognitive subgroups in ROP, ROD and CHR are more informative than transdiagnostic subgroups as they map onto individual cognitive impairment and specific functioning- and symptom-patterns which show limited overlap in sMRI and rsFC.Clinical trial registry nameGerman Clinical Trials Register (DRKS). Clinical trial registry URL: https://www.drks.de/drks_web/. Clinical trial registry number: DRKS00005042.

How brain structure relates to psychopathology across diagnoses in pre‐adolescents

Using data from the federal government's Adolescent Brain Cognitive Development (ABCD) study, researchers have identified specific brain structure features that might contribute to transdiagnostic (across diagnostic categories) psychopathology development in preadolescence. The study found that children with smaller total brain volume and surface area may be vulnerable to persistent general psychopathology during preadolescence. “Cortical thinning reflective of pruning and myelination in sensorimotor and temporal brain regions specifically may protect against increases in internaliz‐ing, but not general psychopathology, during preadolescence,” according to the study. In general, structural neural alterations have been associated with the “p factor” (higher “p” scores are associated with developmental problems and other issues, but not specifically related to diagnoses). However, less is known about how the brain al‐terations relate within time in an individual, especially during preadolescence, when many neurodevelopmental changes are taking place. This study looked at the trajectory of the p factor and specific forms of psychopathology over 2 years in 9,220 preadolescents (aged 9–10 years at baseline). The study found that smaller volume and surface area of the brain, but not thickness, were associated with higher p factor scores which persisted over time in between‐person (how individuals differ) but not within‐person (how change occurs in a particular individual) p factor scores. “Lower baseline cortical thickness was associated with steeper decreases in internalizing psychopathology, which was driven by lower thickness within sensorimotor and temporal regions.” [Romer, A. L., Ren, B., Pizzagalli, D. A. (2023, Feb 9). Brain structure relations with psychopathology trajectories in the Adolescent Brain Cognitive Development Study. J Am Acad Child Adolesc Psychiatry, S0890‐8567(23)00057‐6. http://doi.org/10.1016/j.jaac.2023.02.002.]

Changes in neurotransmitter levels, brain structural characteristics, and their correlation with PANSS scores in patients with first-episode schizophrenia.

In patients with schizophrenia, the brain structure and neurotransmitter levels change, which may be related to the occurrence and progression of this disease. To explore the relationships between changes in neurotransmitters, brain structural characteristics, and the scores of the Positive and Negative Symptom Scale (PANSS) in patients with first-episode schizophrenia. The case group comprised 97 patients with schizophrenia, who were evaluated using the Canadian Neurological Scale and confirmed by laboratory tests at Ningbo Mental Hospital from January 2020 to July 2022. The control group comprised 100 healthy participants. For all participants, brain structural characteristics were explored by measuring brain dopamine (DA), glutamic acid (Glu), and gamma-aminobutyric acid (GABA) levels, with magnetic resonance imaging. The case group was divided into negative and positive symptom subgroups using PANSS scores for hierarchical analysis. Linear correlation analysis was used to analyze the correlations between neurotransmitters, brain structural characteristics, and PANSS scores. Patients in the case group had higher levels of DA and lower levels of Glu and GABA, greater vertical and horizontal distances between the corpus callosum and the inferior part of the fornix and larger ventricle area than patients in the control group (P < 0.05). Patients with positive schizophrenia symptoms had significantly higher levels of DA, Glu, and GABA than those with negative symptoms (P < 0.05). In patients with positive schizophrenia symptoms, PANSS score was significantly positively correlated with DA, vertical and horizontal distances between the corpus callosum and the infrafornix, and ventricular area, and was significantly negatively correlated with Glu and GABA (P < 0.05). In patients with negative schizophrenia symptoms, PANSS score was significantly positively correlated with DA, vertical distance between the corpus callosum and the infrafornix, horizontal distance between the corpus callosum and the infrafornix, and ventricular area, and was significantly negatively correlated with Glu and GABA (P < 0.05). In patients with first-episode schizophrenia, DA levels increased, Glu and GABA levels decreased, the thickness of the corpus callosum increased, and these variables were correlated with PANSS scores.

Changes in neurotransmitter levels, brain structural characteristics, and their correlation with PANSS scores in patients with first-episode schizophrenia

In recent years, because of the growing desire to improve the noninvasiveness and safety of tumor treatments, sonodynamic therapy has gradually become a popular research topic. However, due to the complexity of the therapeutic process, the relevant mechanisms have not yet been fully elucidated. One of the widely accepted possibilities involves the effect of reactive oxygen species. In this review, the mechanism of reactive oxygen species production by sonodynamic therapy (SDT) and ways to enhance the sonodynamic production of reactive oxygen species are reviewed. Then, the clinical application and limitations of SDT are discussed. In conclusion, current research on sonodynamic therapy should focus on the development of sonosensitizers that efficiently produce active oxygen, exhibit biological safety, and promote the clinical transformation of sonodynamic therapy.

Noninvasive disruption of the blood-brain barrier in the marmoset monkey

The common marmoset monkey (Callithrix jacchus) is a species of rising prominence in the neurosciences due to its small size, ease of handling, fast breeding, and its shared functional and structural brain characteristics with Old World primates. With increasing attention on modeling human brain diseases in marmosets, understanding how to deliver therapeutic or neurotropic agents to the marmoset brain noninvasively is of great preclinical importance. In other species, including humans, transcranial focused ultrasound (tFUS) aided by intravenously injected microbubbles has proven to be a transient, reliable, and safe method for disrupting the blood-brain barrier (BBB), allowing the focal passage of therapeutic agents that do not otherwise readily traverse the tight endothelial junctions of the BBB. The critical gap that we address here is to document parameters to disrupt the BBB reliably and safely in marmosets using tFUS. By integrating our marmoset brain atlases and the use of a marmoset-specific stereotactic targeting system, we conduct a series of systematic transcranial sonication experiments in nine marmosets. We demonstrate the effects of center frequency, acoustic pressure, burst period, and duration, establish a minimum microbubble dose, estimate microbubble clearance time, and estimate the duration that the BBB remains open to passage. Successful BBB disruption is reported in vivo with MRI-based contrast agents, as well as Evans blue staining assessed ex vivo. Histology (Hematoxylin and Eosin staining) and immunohistochemistry indicate that the BBB can be safely and reliably opened with the parameters derived from these experiments. The series of experiments presented here establish methods for safely, reproducibly, and focally perturbing the BBB using tFUS in the common marmoset monkey that can serve as a basis for noninvasive delivery of therapeutic or neurotropic agents.