Drinking during pregnancy: Potential role of endocannabinoid signaling in fetal alcohol effects

Alcohol is a well-recognized teratogen that can causevariable physical and behavioral effects on the fetus.Alcohol use and abuse during pregnancy is one of the major health and societal problems and has been linked to a wide range of birth defects in the offspring collectively termed as fetal alcohol spectrum disorder(FASD). The severity of abnormalities may depend on a number of factors that include the amount, the frequency, the period during gestation and the route of alcohol administration. The current knowledge about the neurobiological basis of FASD is limited. However, recent studies have suggested that the membrane-derived lipids especially bioactive endogenous cannabinoids(eCB)such as arachidonyl ethanolamide and 2-arachidonyl glycerol resulting from alcohol exposure, may play a significant role in modulating neurophysiological and neurobehavioral effects in chronic alcohol exposed adult animals. Based on these findings and on reported studies on the role of eCB signaling in neurodevelopment and behavior, it is speculated that the eC B signaling may play a critical role in fetal alcohol syndrome and FASD-related behavioral effects. The current discussion will touch upon some of the mechanistic explanations about the role of eCB signaling system in FASD and provide further guidance for future direction.

A Comparison Study of the Efficacy of Rapid Titration Quetiapine and Haloperidol in Agitated Adults in an Emergency Setting

Objective: Intramuscular (IM) Benzodiazepines and/or Haloperidol alone or with benzodiazepines are frequently used to treat agitation. Based on emerging literature regarding Quetiapine used for the control of anxiety we examined Quetiapine as a possible alternative in selected cases. Methods: This study was a single-blind randomized study comparing Quetiapine PO (300 mg) with a combination of Haloperidol (5 mg), Benztropine mesylate (2 mg) and lorazepam (2 mg) administered IM to treat agitated patients seeking care in a busy psychiatric emergency setting. Male or female patients (18 - 60), deemed by the attending (admitting) psychiatrist to be indicative of agitated and/or aggressive behavior and had a Positive and Negative Syndrome Score-Excited Component (PANSS-EC), as evaluated by the Research Psychiatrist, and total score equal to or greater than 15. Patients deemed competent were randomized into one of the following treatment groups: Quetiapine 300 or Haloperidol 5 mg, benztropine mesylate, or lorazepam given by the IM route. Two scales, PANSS-EC and CGI-C were used to assess patients in the trial. The primary outcome measure PANSS-EC at 2 hours after administration of the medication. Results: Sixty-eight patients were included in the study. There were no significant treatment group differences in baseline condition. There was no significant difference between the two conditions. There was, however, a significant within-group decrease from baseline condition. Conclusion: Finding no significant differences suggests that in general the two treatments were equivalent. To sum up, Quetiapine 300 mg as a single dose appeared safe and effective in agitated patients treated in an ER. The results were similar to a comparison group receiving an intra-muscular combination of Haloperidol, Lorazepam and Benztropine. This study has significant limitations. The study was single blind and the use of a placebo would have strengthened the design but would be considered unethical. The sample size was relatively small and the group of patients who come to the ER may not be representative of the population of patients who visit across the country. And finally it was a select subgroup who made up the study population and who were probably less severely ill than other subjects who came to our ER.

众脑之力:通过开放神经影像数据和大规模协作催化神经精神疾病的创新发现

Recent advances in open neuroimaging data are enhancing our comprehension of neuropsychiatric disorders.By pooling images from various cohorts,statistical power has increased,enabling the detection of subtle abnormalities and robust associations,and fostering new research methods.Global collaborations in imaging have furthered our knowledge of the neurobiological foundations of brain disorders and aided in imaging-based prediction for more targeted treatment.Large-scale magnetic resonance imaging initiatives are driving innovation in analytics and supporting generalizable psychiatric studies.We also emphasize the significant role of big data in understanding neural mechanisms and in the early identification and precise treatment of neuropsychiatric disorders.However,challenges such as data harmonization across different sites,privacy protection,and effective data sharing must be addressed.With proper governance and open science practices,we conclude with a projection of how large-scale imaging resources and collaborations could revolutionize diagnosis,treatment selection,and outcome prediction,contributing to optimal brain health.

Back to the future:Some similarities and many differences between autism spectrum disorder and early onset schizophrenia.Clues to pathophysiology?

In the first issue of the recently launched journal,Medicine Plus,Lu et al.[1]report on a remarkable effort encompassing nearly 600 young participants examined at five centers in China.The focus was on the first episode early-onset schizophrenia(EOS;onset before age 18 years)and autism spectrum disorder(ASD),contrasted to each other and healthy controls(HC).Historically,autism was initially considered a form of infantile schizophrenia,although it was differentiated from early-onset schizophrenia as early as 1955 by Eisenberg and Kanner[2].

Erratum to“The power of many brains:Catalyzing neuropsychiatric discovery through open neuroimaging data and large-scale collaboration”[Sci Bull 2024;69:1536-1555]

The publisher regrets to note that reference citation errors have occurred in panels b,c,e-l in Fig 2 and the sentence“However,the literature reports both decreased and increased intra-network functional connections among patients with depression[115,116].”The publisher would like to apologise for any inconvenience caused.Fig.2.Principal neuroimaging findings in major depressive disorder.(a)Decreased intra-DMN FC is observed in recurrent MDD patients[35].(b)Eight-week antidepressant treatment reduce extensive large-scale functional networks[107].(c)Reduced global and local efficiency(Eglob/Eloc)are revealed in MDD patients[108].(d)Structural variations of the cortex and subcortical nuclei are found in ENIGMA-MDD studies[82].(e)Accelerated brain aging based on functional MRI is observed in MDD patients[114].(f)Accelerated brain aging based on structural MRI is observed in MDD patients[115].(g)Two subtypes of MDD can be identified through DMN FC[127].(h)A significant schizophrenia PRS by MDD interaction for rostral anterior cingulate cortex thickness is found in the UK Biobank dataset[215].(i)Stability of the four MDD subtypes based on FC[126].(j)The two subtypes of MDD exhibit distinct patterns of FC within and between SMS,DMN,and subcortical structures[130].(k)Performance of the functional connectivity-based classifiers across two multicenter datasets[135].(l)Salient brain regions that serve as important classification features for the graph convolutional network-based classifier[136].Brain-PAD:brain-predicted age difference;DAN:dorsal attention network;DMN:default mode network;FC:functional connectivity;FEDN:first-episode and drug-naïve;FPN:frontoparietal network;GCN:graph convolutional neural network;HC:healthy control;linear-SVM:linear support vector machine;MDD:major depressive disorder;mddrest:REST-meta-MDD dataset;NC:normal control;RACC:rostral anterior cingulate cortex;PRS:polygenic risk score;psymri:PsyMRI dataset;rbf-SVM:radial basis function support vector machine;SCN:subcortical network;SCZ:schizophrenia;SMN:sensorimotor network;SMS:sensory and motor systems;SubC:subcortical network;VAN:ventral attention network;VN:visual network.

Concordance among indices of intrinsic brain function： Insights from inter-individual variation and temporal dynamics

Various resting-state fMRI(R-fMRI) measures have been developed to characterize intrinsic brain activity. While each of these measures has gained a growing presence in the literature, questions remain regarding the common and unique aspects these indices capture. The present work provided a comprehensive examination of inter-individual variation and intra-individual temporal variation for commonly used measures, including fractional amplitude of low frequency fluctuations, regional homogeneity,voxel-mirrored homotopic connectivity, network centrality and global signal correlation. Regardless of whether examining intra-individual or inter-individual variation, we found that these definitionally distinct R-fMRI indices tend to exhibit a relatively high degree of covariation, which doesn't exist in phase randomized surrogate data. As a measure of intrinsic brain function, concordance for R-fMRI indices was negatively correlated with age across individuals(i.e., concordance among functional indices decreased with age). To understand the functional significance of concordance, we noted that higher concordance was generally associated with higher strengths of R-fMRI indices, regardless of whether looking through the lens of inter-individual(i.e., high vs. low concordance participants) or intra-individual(i.e., high vs.low concordance states identified via temporal dynamic analyses) differences. We also noted a linear increase in functional concordance together with the R-fMRI indices through the scan, which may suggest a decrease in arousal. The current study demonstrated an enriched picture regarding the relationship among the R-fMRI indices, as well as provided new insights in examining dynamic states within and between individuals.

Low-frequency fluctuation in continuous real-time feedback of finger force:a new paradigm for sustained attention

Objective Behavioral studies have suggested a low-frequency（0.05 Hz） fluctuation of sustained attention on the basis of the intra-individual variability of reaction-time.Conventional task designs for functional magnetic resonance imaging（fMRI） studies are not appropriate for frequency analysis.The present study aimed to propose a new paradigm,real-time finger force feedback（RT-FFF）,to study the brain mechanisms of sustained attention and neurofeedback.Methods We compared the low-frequency fluctuations in both behavioral and fMRI data from 38 healthy adults（19 males;mean age,22.3 years）.Two fMRI sessions,in RT-FFF and sham finger force feedback（S-FFF） states,were acquired（TR 2 s,Siemens Trio 3-Tesla scanner,8 min each,counter-balanced）.Behavioral data of finger force were obtained simultaneously at a sampling rate of 250 Hz.Results Frequency analysis of the behavioral data showed lower amplitude in the lowfrequency band（0.004-0.104 Hz） but higher amplitude in the high-frequency band（27.02-125 Hz） in the RT-FFF than the S-FFF states.The mean finger force was not significantly different between the two states.fMRI data analysis showed higher fractional amplitude of low-frequency fluctuation（fALFF） in the S-FFF than in the RT-FFF state in the visual cortex,but higher fALFF in RT-FFF than S-FFF in the middle frontal gyrus,the superior frontal gyrus,and the default mode network.Conclusion The behavioral results suggest that the proposed paradigm may provide a new approach to studies of sustained attention.The fMRI results suggest that a distributed network including visual,motor,attentional,and default mode networks may be involved in sustained attention and/or real-time feedback.This paradigm may be helpful for future studies on deficits of attention,such as attention deficit hyperactivity disorder and mild traumatic brain injury.

Charting brain growth in tandem with brain templates at school age

Brain growth charts and age-normed brain templates are essential resources for researchers to eventually contribute to the care of individuals with atypical developmental trajectories.The present work generates age-normed brain templates for children and adolescents at one-year intervals and the corresponding growth charts to investigate the influences of age and ethnicity using a common pediatric neuroimaging protocol.Two accelerated longitudinal cohorts with the identical experimental design were implemented in the United States and China.Anatomical magnetic resonance imaging(MRI)of typically developing school-age children(TDC)was obtained up to three times at nominal intervals of1.25 years.The protocol generated and compared population-and age-specific brain templates and growth charts,respectively.A total of 674 Chinese pediatric MRI scans were obtained from 457 Chinese TDC and 190 American pediatric MRI scans were obtained from 133 American TDC.Population-and age-specific brain templates were used to quantify warp cost,the differences between individual brains and brain templates.Volumetric growth charts for labeled brain network areas were generated.Shape analyses of cost functions supported the necessity of age-specific and ethnicitymatched brain templates,which was confirmed by growth chart analyses.These analyses revealed volumetric growth differences between the two ethnicities primarily in lateral frontal and parietal areas,regions which are most variable across individuals in regard to their structure and function.Age-and ethnicity-specific brain templates facilitate establishing unbiased pediatric brain growth charts,indicating the necessity of the brain charts and brain templates generated in tandem.These templates and growth charts as well as related codes have been made freely available to the public for open neuroscience(https://github.com/zuoxinian/CCS/tree/master/H3/Growth Charts).

The DIRECT consortium and the REST-meta-MDD project:towards neuroimaging biomarkers of major depressive disorder

Despite a growing neuroimaging literature on the pathophysiology of major depressive disorder(MDD),repro-ducible findings are lacking,probably reflecting mostly small sample sizes and heterogeneity in analytic approaches.To address these issues,the Depression Imaging REsearch ConsorTium(DIRECT)was launched.The REST-meta-MDD project,pooling 2428 functional brain images processed with a standardized pipeline across all participating sites,has been the first effort from DIRECT.In this review,we present an overview of the moti-vations,rationale,and principal findings of the studies so far from the REST-meta-MDD project.Findings from the first round of analyses of the pooled repository have included alterations in functional connectivity within the default mode network,in whole-brain topological properties,in dynamic features,and in functional lat-eralization.These well-powered exploratory observations have also provided the basis for future longitudinal hypothesis-driven research.Following these fruitful explorations,DIRECT has proceeded to its second stage of data sharing that seeks to examine ethnicity in brain alterations in MDD by extending the exclusive Chinese original sample to other ethnic groups through international collaborations.A state-of-the-art,surface-based preprocessing pipeline has also been introduced to improve sensitivity.Functional images from patients with bipolar disorder and schizophrenia will be included to identify shared and unique abnormalities across diag-nosis boundaries.In addition,large-scale longitudinal studies targeting brain network alterations following antidepressant treatment,aggregation of diffusion tensor images,and the development of functional magnetic resonance imaging-guided neuromodulation approaches are underway.Through these endeavours,we hope to accelerate the translation of functional neuroimaging findings to clinical use,such as evaluating longitudinal effects of antidepressant medications and developing individualized neuromodulation targets,while building an open repository for the scientific community.