Background The heterogeneity of depression limits the treatment outcomes of intermittent theta burst stimulation(iTBS)and hinders the identification of predictive factors.This study investigated functional network con...Background The heterogeneity of depression limits the treatment outcomes of intermittent theta burst stimulation(iTBS)and hinders the identification of predictive factors.This study investigated functional network connectivity and predictors of iTBS treatment outcomes in adolescents and young adults with depression.Aim This study aimed to identify default mode network(DMN)-based connectivity patterns associated with varying iTBS treatment outcomes in depression.Methods Data from a randomised controlled trial of iTBS in depression(n=82)were analysed using a data-driven approach to classify homogeneous subgroups based on the DMN.Connectivity subgroups were compared on depressive symptoms and cognitive function at pretreatment and post-treatment.Furthermore,the predictive significance of baseline inflammatory cytokines on post-treatment outcomes was evaluated.Results Two distinct subgroups were identified.Subgroup 1 exhibited high heterogeneity and greater centrality in the posterior cingulate cortex and retrosplenial cortex,while subgroup 2 showed more homogeneous connectivity patterns and greater centrality in the temporoparietal junction and posterior inferior parietal lobule.No main effect for subgroup,treatment or subgroup×treatment interaction was revealed in the improvement of depressive symptoms.A significant subgroup×treatment interaction related to symbol coding improvement was detected(F=5.22,p=0.026).Within subgroup 1,the active group showed significantly greater improvement in symbol coding compared with the sham group(t=2.30,p=0.028),while baseline levels of interleukin-6 and C-reactive protein emerged as significant indicators for predicting improvements in symbolic coding(R2=0.35,RMSE(root-mean-square error)=5.72,p=0.013).Subgroup 2 showed no significant findings in terms of cognitive improvement or inflammatory cytokines predictions.展开更多
Chimpanzees(Pan troglodytes)are one of humans'closest living relatives,making them the most directly relevant comparison point for understanding human brain evolution.Zeroing in on the differences in brain connect...Chimpanzees(Pan troglodytes)are one of humans'closest living relatives,making them the most directly relevant comparison point for understanding human brain evolution.Zeroing in on the differences in brain connectivity between humans and chimpanzees can provide key insights into the specific evolutionary changes that might have occurred along the human lineage.However,such comparisons are hindered by the absence of cross-species brain atlases established within the same framework.To address this gap,we developed the Chimpanzee Brainnetome Atlas(ChimpBNA)using a connectivity-based parcellation framework.Leveraging this new resource,we found substantial divergence in connectivity patterns between the two species across most association cortices,notably in the lateral temporal and dorsolateral prefrontal cortex.These differences deviate sharply from the pattern of cortical expansion observed when comparing humans to chimpanzees,highlighting more complex and nuanced connectivity changes in brain evolution than previously recognized.Additionally,we identified regions displaying connectional asymmetries that differed between species,likely resulting from evolutionary divergence.Genes highly expressed in regions of divergent connectivities were enriched in cell types crucial for cortical projection circuits and synapse formation,whose pronounced differences in expression patterns hint at genetic influences on neural circuit development,function,and evolution.Our study provides a fine-scale chimpanzee brain atlas and highlights the chimpanzee-human connectivity divergence in a rigorous and comparative manner.In addition,these results suggest potential gene expression correlates for species-specific differences by linking neuroimaging and genetic data,offering insights into the evolution of human-unique cognitive capabilities.展开更多
Background： Electroconvulsive therapy （ECT） can alleviate the symptoms of treatment-resistant depression （TRD）. Functional network connectivity （FNC） is a newly developed method to investigate the brain＇s func...Background： Electroconvulsive therapy （ECT） can alleviate the symptoms of treatment-resistant depression （TRD）. Functional network connectivity （FNC） is a newly developed method to investigate the brain＇s functional connectivity patterns. The first aim of this study was to investigate FNC alterations between TRD patients and healthy controls. The second aim was to explore the relationship between the ECT treatment response and pre-ECT treatment FNC alterations in individual TRD patients. Methods： This study included 82 TRD patients and 41 controls. Patients were screened at baseline and after 2 weeks of treatment with a combination of ECT and antidepressants. Group information guided-independent component analysis （G1G-ICA） was used to compute subject-specific functional networks （FNs）. Grassmann maniibld and step-wise forward component selection using support vector machines were adopted to perform the FNC measure and extract the functional networks＇ connectivity patterns （FCP）. Pearson＇s correlation analysis was used to calculate the correlations between the FCP and ECT response. Results： A total of 82 TRD patients in the ECT group were successfully treated. On an average, 8.50 ~ 2.00 ECT sessions were conducted. After ECT treatment, only 42 TRD patients had an improved response to ECT （the Hamilton scores reduction rate was more than 50%）, response rate 51%. 8 FNs （anterior and posterior default mode network, bilateral frontoparietal network, audio network, visual network, dorsal attention network, and sensorimotor network） were obtained using GIG-ICA. We did not found that FCPs were significantly different between TRD patients and healthy controls. Moreover, the baseline FCP was unrelated to the ECT treatment response. Conclusions： The FNC was not significantly different between the TRD patients and healthy controls, and the baseline FCP was unrelated to the ECT treatment response. These findings will necessitate that we modify the experimental scheme to explore the mechanisms underlying ECT＇s effects on depression and explore the specific predictors of the effects of ECT based on the pre-ECT treatment magnetic resonance imaging.展开更多
基金supported by the Guangzhou Municipal Key Discipline in Medicine(2021-2023)the Guangzhou High-level Clinical Key Specialty,the Guangzhou Research-oriented Hospital,the Innovative Clinical Technique of Guangzhou(2024-2026)+6 种基金the Guangdong Basic and Applied Basic Research Foundation(grant number 2022A1515011567,2020A1515110565)the Guangzhou Science,Technology Planning Project(grant number 202201010714,202103000032)the National Natural Science Foundation of China(grant number 82471546)the Guangdong College Students Innovation and Entrepreneurship Training Project(grant number S202310570038)the Guangzhou Health Science and Technology Project(grant number 20231A010038)the Guangzhou Traditional Chinese Medicine and Integrated Traditional Chinese and Western Medicine Technology Project(grant number:20232A010013)the Science and Technology Plan Project of Guangzhou(2023A03J0842).
文摘Background The heterogeneity of depression limits the treatment outcomes of intermittent theta burst stimulation(iTBS)and hinders the identification of predictive factors.This study investigated functional network connectivity and predictors of iTBS treatment outcomes in adolescents and young adults with depression.Aim This study aimed to identify default mode network(DMN)-based connectivity patterns associated with varying iTBS treatment outcomes in depression.Methods Data from a randomised controlled trial of iTBS in depression(n=82)were analysed using a data-driven approach to classify homogeneous subgroups based on the DMN.Connectivity subgroups were compared on depressive symptoms and cognitive function at pretreatment and post-treatment.Furthermore,the predictive significance of baseline inflammatory cytokines on post-treatment outcomes was evaluated.Results Two distinct subgroups were identified.Subgroup 1 exhibited high heterogeneity and greater centrality in the posterior cingulate cortex and retrosplenial cortex,while subgroup 2 showed more homogeneous connectivity patterns and greater centrality in the temporoparietal junction and posterior inferior parietal lobule.No main effect for subgroup,treatment or subgroup×treatment interaction was revealed in the improvement of depressive symptoms.A significant subgroup×treatment interaction related to symbol coding improvement was detected(F=5.22,p=0.026).Within subgroup 1,the active group showed significantly greater improvement in symbol coding compared with the sham group(t=2.30,p=0.028),while baseline levels of interleukin-6 and C-reactive protein emerged as significant indicators for predicting improvements in symbolic coding(R2=0.35,RMSE(root-mean-square error)=5.72,p=0.013).Subgroup 2 showed no significant findings in terms of cognitive improvement or inflammatory cytokines predictions.
基金supported by ST12030-Major Projects(grant na 2021ZD0200203)the Natural Science Foundation of China(grant nos.82072099,82202253,and 62250058)the China Postdoctoral Science Foundation(2022M722915)+1 种基金the Guangxi Science and Technology Base and Talent Special Project(grant no AD22035125)Chongqing Science and Health Joint Medical Research Key Project(2025GGXM005).
文摘Chimpanzees(Pan troglodytes)are one of humans'closest living relatives,making them the most directly relevant comparison point for understanding human brain evolution.Zeroing in on the differences in brain connectivity between humans and chimpanzees can provide key insights into the specific evolutionary changes that might have occurred along the human lineage.However,such comparisons are hindered by the absence of cross-species brain atlases established within the same framework.To address this gap,we developed the Chimpanzee Brainnetome Atlas(ChimpBNA)using a connectivity-based parcellation framework.Leveraging this new resource,we found substantial divergence in connectivity patterns between the two species across most association cortices,notably in the lateral temporal and dorsolateral prefrontal cortex.These differences deviate sharply from the pattern of cortical expansion observed when comparing humans to chimpanzees,highlighting more complex and nuanced connectivity changes in brain evolution than previously recognized.Additionally,we identified regions displaying connectional asymmetries that differed between species,likely resulting from evolutionary divergence.Genes highly expressed in regions of divergent connectivities were enriched in cell types crucial for cortical projection circuits and synapse formation,whose pronounced differences in expression patterns hint at genetic influences on neural circuit development,function,and evolution.Our study provides a fine-scale chimpanzee brain atlas and highlights the chimpanzee-human connectivity divergence in a rigorous and comparative manner.In addition,these results suggest potential gene expression correlates for species-specific differences by linking neuroimaging and genetic data,offering insights into the evolution of human-unique cognitive capabilities.
文摘Background： Electroconvulsive therapy （ECT） can alleviate the symptoms of treatment-resistant depression （TRD）. Functional network connectivity （FNC） is a newly developed method to investigate the brain＇s functional connectivity patterns. The first aim of this study was to investigate FNC alterations between TRD patients and healthy controls. The second aim was to explore the relationship between the ECT treatment response and pre-ECT treatment FNC alterations in individual TRD patients. Methods： This study included 82 TRD patients and 41 controls. Patients were screened at baseline and after 2 weeks of treatment with a combination of ECT and antidepressants. Group information guided-independent component analysis （G1G-ICA） was used to compute subject-specific functional networks （FNs）. Grassmann maniibld and step-wise forward component selection using support vector machines were adopted to perform the FNC measure and extract the functional networks＇ connectivity patterns （FCP）. Pearson＇s correlation analysis was used to calculate the correlations between the FCP and ECT response. Results： A total of 82 TRD patients in the ECT group were successfully treated. On an average, 8.50 ~ 2.00 ECT sessions were conducted. After ECT treatment, only 42 TRD patients had an improved response to ECT （the Hamilton scores reduction rate was more than 50%）, response rate 51%. 8 FNs （anterior and posterior default mode network, bilateral frontoparietal network, audio network, visual network, dorsal attention network, and sensorimotor network） were obtained using GIG-ICA. We did not found that FCPs were significantly different between TRD patients and healthy controls. Moreover, the baseline FCP was unrelated to the ECT treatment response. Conclusions： The FNC was not significantly different between the TRD patients and healthy controls, and the baseline FCP was unrelated to the ECT treatment response. These findings will necessitate that we modify the experimental scheme to explore the mechanisms underlying ECT＇s effects on depression and explore the specific predictors of the effects of ECT based on the pre-ECT treatment magnetic resonance imaging.
