Explore the vast range of titles available.

Studies of Internet gaming disorder (IGD) suggest an imbalanced relationship between cognitive control and reward processing in people with IGD. However, it remains unclear how these two systems interact with each other, and whether they could serve as neurobiological markers for IGD. Fifty IGD subjects and matched individuals with recreational game use (RGU) were selected and compared when they were performing a cue-craving task. Regions of interests [anterior cingulate cortex (ACC), lentiform nucleus] were selected based on the comparison between brain responses to gaming-related cues and neutral cues. Directional connectivities among these brain regions were determined using Bayesian estimation. We additionally examined the posterior cingulate cortex (PCC) in a separate analysis based on data implicating the PCC in craving in addiction. During fixed-connectivity analyses, IGD subjects showed blunted ACC-to-lentiform and lentiform-to-ACC connectivity relative to RGU subjects, especially in the left hemisphere. When facing gaming cues, IGD subjects trended toward lower left-hemispheric modulatory effects in ACC-to-lentiform connectivity than RGU subjects. Self-reported cue-related craving prior to scanning correlated inversely with left-hemispheric modulatory effects in ACC-to-lentiform connectivity. The results suggesting that prefrontal-to-lentiform connectivity is impaired in IGD provides a possible neurobiological mechanism for difficulties in controlling gaming-cue-elicited cravings. Reduced connectivity ACC-lentiform connectivity may be a useful neurobiological marker for IGD.

As we human beings are living in a multidimensional space all the time. Therefore, spatial ability is vital for the survival and development of individuals. However, males and females show gender differences in this ability. So, are these gender differences influenced by the scale type of spatial ability? It's not well specified. Therefore, to tackle this issue, we conducted the current research from the behavioral and neural level. Study 1 used the general meta-analysis method to explore whether individuals display the same gender differences in large- and small-scale spatial ability. Study 2 used the method of Activation Likelihood Estimation to identify the commonalities and distinctions of the brain activity between males and females on large- and small-scale spatial ability. Study 1 showed that in behavior performance, males outperformed females in both large-scale and small-scale spatial ability, but the effect size of the gender difference in large-scale spatial ability is significantly greater than that in small-scale spatial ability. In addition, Study 2 showed that in terms of neural activity, males and females exhibited both similarities and differences no matter in large-scale or small-scale spatial ability. Especially, the contrast analysis between females and males demonstrated a stronger activation in the brain regions of bilateral lentiform nucleus and bilateral parahippocampal gyrus in large-scale spatial ability, and correspondence in right sub-gyral, right precuneus, and left middle frontal gyrus in small-scale spatial ability. The results indicated that the reason why females performed not so well in large-scale spatial ability was that they were more susceptible to emotions and their parahippocampal gyrus worked less efficiently than males; females performed not so well in small-scale spatial ability because they mostly adopted the egocentric strategy and their sub-gyral also worked less efficiently than males. The two different reasons have made for gender differences in favor of males in terms of spatial ability and such gender differences have different manifestations in large-scale and small-scale spatial ability. Possible implications of the results for understanding the issue of gender differences in spatial ability are discussed.

To investigate the characteristics of brain region activation associated with explicit outcome expectation effects in treatment contexts, and to identify core brain regions consistently involved across diverse experimental paradigms. A systematic search was conducted for studies published from January 1, 2014, to December 31, 2025. Functional magnetic resonance imaging (fMRI) and positron emission tomography (PET) studies investigating treatment expectation effects were included. In neuroimaging paradigms, these effects are commonly induced through explicit outcome expectations via verbal instructions or contextual cues. Risk of bias was assessed using the ROB 2.0 and ROBINS‐I tools. Activation likelihood estimation (ALE) meta‐analysis was performed using GingerALE 3.0.2 based on whole‐brain activation coordinates. Results were visualized using Mango software. Sensitivity analyses were performed by excluding the study with the highest risk of bias and using a leave‐one‐study‐out approach. Additionally, a qualitative synthesis of activation foci was conducted across four domains to address paradigm heterogeneity. A total of 21 articles with 855 subjects were included in this study, consisting of 17 randomized controlled trials and 4 non‐randomized studies. The risk of bias assessment indicated that only five RCTs were rated as low risk, while approximately three‐quarters of studies showed some concerns or high risk. Most studies modulated expectations through interventions such as verbal instruction and pain stimulation. Convergent neuroimaging studies implicated the insula, frontal lobe, striatum, and additional relevant brain regions. The ALE meta‐analysis identified two significant activation clusters located in the caudate nucleus/lentiform nucleus and the red nucleus. Sensitivity analyses indicated that the majority of findings remained stable. Qualitative domain‐based synthesis further revealed consistent striatal activation across all domains, together with distinct domain‐specific activation patterns. The findings of this study suggest that explicit outcome expectation effects, as a core operationalized component of treatment expectation, do not rely on a single brain region but emerge from distributed and dynamically interacting neural systems that depend on reward expectation and information integration. The coordinated activity of multiple brain regions collectively supports the generation of explicit outcome expectations. The striatum serves as a shared core substrate across different expectancy domains, while domain‐specific activation reflects functional specialization for distinct contexts. These findings provide important evidence for elucidating the neural correlates of explicit outcome expectation effects and establish a foundation for further brain mechanism‐based intervention strategies. Trial Registration: PROSPERO: CRD420251074894 Key Points Using an integrative ALE approach, this study provided a systematic and consistent characterization of brain activation patterns associated with explicit outcome expectations in treatment contexts. This meta‐analysis identified the caudate nucleus/lentiform nucleus as a core neural substrate with the red nucleus emerging as an additional significant cluster. This ALE meta‐analysis of brain imaging studies published between 2014 and 2025 identified the caudate nucleus/lentiform nucleus as a core neural substrate of explicit outcome expectation effects, with the red nucleus emerging as an additional significant cluster.

Final infarct volume (FIV) is a strong predictor of stroke outcomes. Although smaller FIV are associated with better outcomes, many patients fail to achieve functional independence. We aimed to identify poor outcome predictors in patients with anterior large vessel occlusion stroke (LVOS) who underwent mechanical thrombectomy (MT) and had small FIV. We reviewed a prospective MT database from October 2010 to December 2020. Patients with intracranial ICA or MCA-M1/2 occlusions, premorbid mRS ≤ 2, underwent MT, and had FIV ≤ 30 ml on follow-up MRI were included. The cohort was divided into: good (mRS≤2) and poor (mRS>2) outcomes at 90 days. Multivariable analysis identified the poor outcome predictors and the association between e-ASPECTS regions and outcomes. Among 2370 thrombectomies, 555 had FIV ≤ 30 ml. After exclusions, 398 patients were analyzed. The median age was 65 years, with 54 % female, median NIHSS was 15, and the median ASPECTS was 9. Poor outcome was associated with older age, female sex, atrial fibrillation (AF), hypertension (HTN), coronary artery disease (CAD), and prior strokes. Right lentiform nucleus involvement is an independent predictor of poor outcome in patients with small FIV, along with age, CAD, cardioembolic stroke, number of MT attempts and FIV. Involvement of right lentiform nucleus is an independent predictor of poor outcomes in LVOS with small FIV. Other predictors included age, CAD, cardioembolic stroke, the number of passes during MT, and FIV. Future strategies are needed to improve outcomes in these patient populations. •Small final infarct volume (FIV) was achieved following successful thrombectomy. However, 30 % of the patients had poor outcome at 3 months.•There is no current definition of a small FIV; in this study, two thresholds were used: <30 ml and <10.88 ml, the latter representing the 25th percentile of the cohort.•Poor outcome predictors included age, coronary artery disease, history of stroke, cardioembolic etiology, and number of passes during thrombectomy.•Right lentiform nucleus is an independent predictor of poor outcome in patients with FIV ≤30 ml and also those with FIV<10.88 ml.

Dysphagia is a major cause of stroke infection and death, and identification of structural and functional brain area changes associated with post-stroke dysphagia (PSD) can help in early screening and clinical intervention. Studies on PSD have reported numerous structural lesions and functional abnormalities in brain regions, and a systematic review is lacking. We aimed to integrate several neuroimaging studies to summarize the empirical evidence of neurological changes leading to PSD. We conducted a systematic review of studies that used structural neuroimaging and functional neuroimaging approaches to explore structural and functional brain regions associated with swallowing after stroke, with additional evidence using a live activation likelihood estimation (ALE) approach. A total of 35 studies were included, including 20 studies with structural neuroimaging analysis, 14 studies with functional neuroimaging analysis and one study reporting results for both. The overall results suggest that structural lesions and functional abnormalities in the sensorimotor cortex, insula, cerebellum, cingulate gyrus, thalamus, basal ganglia, and associated white matter connections in individuals with stroke may contribute to dysphagia, and the ALE analysis provides additional evidence for structural lesions in the right lentiform nucleus and right thalamus and functional abnormalities in the left thalamus. Our findings suggest that PSD is associated with neurological changes in brain regions such as sensorimotor cortex, insula, cerebellum, cingulate gyrus, thalamus, basal ganglia, and associated white matter connections. Adequate understanding of the mechanisms of neural changes in the post-stroke swallowing network may assist in clinical diagnosis and provide ideas for the development of new interventions in clinical practice.

Functional magnetic resonance imaging (fMRI) has revealed inconsistent neural activity patterns in major depressive disorder (MDD) across cognitive and affective domains, and this study used an activation likelihood estimation (ALE) meta-analysis to examine brain function abnormalities in working memory, reward processing, and emotion processing. A systematic search was conducted in PubMed, Embase, Web of Science, ScienceDirect, and CNKI for fMRI studies comparing MDD patients with healthy controls (HCs), including data up to 3 December 2024. ALE meta-analysis was performed to examine activation patterns. Jackknife sensitivity analysis, risk of bias, and Newcastle-Ottawa scale were used to assess robustness and publication bias. Meta-regression analyses were conducted to explore the impact of covariates on the results. Sixty-nine studies (2,073 MDD individuals and 2,009 HCs) were included. MDD individuals showed hyperactivation in the bilateral parahippocampal gyrus, subcallosal gyrus, lentiform nucleus, left claustrum, insula, and anterior cingulate cortex, alongside hypoactivation in the right lentiform nucleus, parahippocampal gyrus, fusiform gyrus, and other regions. Domain-specific analyses revealed working memory-related hyperactivation in the right middle and superior frontal gyrus, reward-related hyperactivation in the bilateral lentiform nucleus, right claustrum, and left caudate, and emotion-related hyperactivation in the bilateral parahippocampal gyrus, bilateral lentiform nucleus, right subcallosal gyrus, right anterior cingulate cortex, and left claustrum. Jackknife sensitivity analysis confirmed robustness, with no significant publication bias or covariate impact. Aberrant activation in the lentiform and caudate nuclei across reward and emotion tasks suggests striatal dysfunction plays a key role in emotion-motivation interplay, highlighting the striatum as a potential target for future therapies.

This work presents detailed anatomic labels for a spatiotemporal atlas of fetal brain Diffusion Tensor Imaging (DTI) between 23 and 30 weeks of post‐conceptional age. Additionally, we examined developmental trajectories in fractional anisotropy (FA) and mean diffusivity (MD) across gestational ages (GA). We performed manual segmentations on a fetal brain DTI atlas. We labeled 14 regions of interest (ROIs): cortical plate (CP), subplate (SP), Intermediate zone‐subventricular zone‐ventricular zone (IZ/SVZ/VZ), Ganglionic Eminence (GE), anterior and posterior limbs of the internal capsule (ALIC, PLIC), genu (GCC), body (BCC), and splenium (SCC) of the corpus callosum (CC), hippocampus, lentiform Nucleus, thalamus, brainstem, and cerebellum. A series of linear regressions were used to assess GA as a predictor of FA and MD for each ROI. The combination of MD and FA allowed the identification of all ROIs. Increasing GA was significantly associated with decreasing FA in the CP, SP, IZ/SVZ/IZ, GE, ALIC, hippocampus, and BCC (p < .03, for all), and with increasing FA in the PLIC and SCC (p < .002, for both). Increasing GA was significantly associated with increasing MD in the CP, SP, IZ/SVZ/IZ, GE, ALIC, and CC (p < .03, for all). We developed a set of expert‐annotated labels for a DTI spatiotemporal atlas of the fetal brain and presented a pilot analysis of developmental changes in cerebral microstructure between 23 and 30 weeks of GA.

To examine whether subacute stroke patients would exhibit abnormal dynamic characteristics of brain activity relative to healthy controls (HC) and to investigate whether the altered dynamic regional indexes were associated with clinical behavior in stroke patients. The dynamic amplitude of low-frequency fluctuations (dALFF) and dynamic regional homogeneity (dReHo) in 42 subacute stroke patients and 55 healthy controls were compared. Correlation analyses between dALFF and dReHo in regions showing significant intergroup differences and clinical scores (i.e., the National Institutes of Health Stroke Scale, Fugl-Meyer assessment and lesion volume size) were conducted in stroke patients. Receiver operating characteristic (ROC) curve analysis was used to determine the potential value of altered dynamic regional indexes to identify stroke patients. Significantly dALFF in the bilateral cerebellum posterior lobe (CPL), ipsilesional superior parietal lobe, ipsilesional inferior temporal gyrus (ITG), the midline supplementary motor area (SMA), ipsilesional putamen and lentiform nucleus were detected in stroke patients compared to HC. Relative to the HC group, the stroke patients showed significant differences in dReHo in the contralesional rectal gyrus, contralesional ITG, contralesional pons, ipsilesional middle frontal gyrus (MFG). Significant correlations between dALFF variability in midline SMA and Fugl-Meyer assessment (FMA) scores or between dReHo variability in the ipsilesional MFG and FMA scores were detected in stroke patients. Furthermore, the ROC curve revealed that dynamic ALFF at SMA and ReHo at ipsilesional MFG might have the potential to distinguish stroke patients. The pattern of intrinsic brain activity variability is altered in stroke patients compared with HC, and dynamic ALFF/ReHo might be potential tools to assess stroke patients' motor function.

This study created an image-to-image translation model that synthesizes diffusion tensor images (DTI) from conventional diffusion weighted images, and validated the similarities between the original and synthetic DTI. Thirty-two healthy volunteers were prospectively recruited. DTI and DWI were obtained with six and three directions of the motion probing gradient (MPG), respectively. The identical imaging plane was paired for the image-to-image translation model that synthesized one direction of the MPG from DWI. This process was repeated six times in the respective MPG directions. Regions of interest (ROIs) in the lentiform nucleus, thalamus, posterior limb of the internal capsule, posterior thalamic radiation, and splenium of the corpus callosum were created and applied to maps derived from the original and synthetic DTI. The mean values and signal-to-noise ratio (SNR) of the original and synthetic maps for each ROI were compared. The Bland–Altman plot between the original and synthetic data was evaluated. Although the test dataset showed a larger standard deviation of all values and lower SNR in the synthetic data than in the original data, the Bland–Altman plots showed each plot localizing in a similar distribution. Synthetic DTI could be generated from conventional DWI with an image-to-image translation model.

Background: Cognitive behavioral therapy (CBT) stands as a highly efficacious psychological treatment for both anxiety and depressive disorders. Nonetheless, scholarly debates persist regarding the specificities of brain area activation during CBT treatment for these disorders. Methodology: Utilizing activation likelihood estimation (ALE) analysis, this study aims to discern the neurobiological similarities and disparities between CBT’s effects on anxiety and depressive disorders by examining functional brain areas. Results: A total of 22 articles, encompassing 443 patients, were included in the meta‐analysis. Our results show that in the resting state, patients with depression treated with CBT resulted in increased activation of the right and left ventral anterior cingulate cortex (vACC), left parahippocampal gyrus (PG), right subgyral, left inferior temporal gyrus (ITG), and right inferior occipital gyrus (IOG), whereas patients with anxiety disorders had increased activation of the right and left superior frontal gyrus (SFG) and decreased activation of the caudate after treatment. In the task state, increased activation of the right PG, right orbital frontal lobe, and right dorsal anterior cingulate cortex (dACC) was mainly observed after treatment in patients with anxiety disorders, and the left lentiform nucleus (LN), left dorsal entorhinal cortex, and right caudate activation were decreased. For depressive disorders, no consistent activation patterns emerged in the task state, likely due to limited studies or heterogeneity in task paradigms across included studies. Conclusion: CBT’s efficacy relies on both shared (e.g., vACC‐mediated emotion regulation and cognitive control) and distinct neural mechanisms (fear‐circuit modulation in anxiety vs. memory‐network enhancement in depression), informing biomarker‐driven treatment personalization.