Petra V Viher, Johanna Seitz-Holland, Marc S Schulz, Elizabeth A Kensinger, Sarina Karmacharya, Talis Swisher, Amanda E Lyall, Nikos Makris, Sylvain Bouix, Martha E Shenton, Marek Kubicki, Robert J Waldinger
{"title":"More organized white matter is associated with positivity bias in older adults.","authors":"Petra V Viher, Johanna Seitz-Holland, Marc S Schulz, Elizabeth A Kensinger, Sarina Karmacharya, Talis Swisher, Amanda E Lyall, Nikos Makris, Sylvain Bouix, Martha E Shenton, Marek Kubicki, Robert J Waldinger","doi":"10.1007/s11682-024-00850-5","DOIUrl":"10.1007/s11682-024-00850-5","url":null,"abstract":"<p><p>On average, healthy older adults prefer positive over neutral or negative stimuli. This positivity bias is related to memory and attention processes and is linked to the function and structure of several interconnected brain areas. However, the relationship between the positivity bias and white matter integrity remains elusive. The present study examines how white matter organization relates to the degree of the positivity bias among older adults. We collected imaging and behavioral data from 25 individuals (12 females, 13 males, and a mean age of 77.32). Based on a functional memory task, we calculated a Pos-Neg score, reflecting the memory for positively valenced information over negative information, and a Pos-Neu score, reflecting the memory for positively valenced information over neutral information. Diffusion-weighted magnetic resonance imaging data were processed using Tract-Based Spatial Statistics. We performed two non-parametric permutation tests to correlate whole brain white matter integrity and the Pos-Neg and Pos-Neu scores while controlling for age, sex, and years of education. We observed a statistically significant positive association between the Pos-Neu score and white matter integrity in multiple brain connections, mostly frontal. The results did not remain significant when including verbal episodic memory as an additional covariate. Our study indicates that the positivity bias in memory in older adults is associated with more organized white matter in the connections of the frontal brain. While these frontal areas are critical for memory and executive processes and have been related to pathological aging, more extensive studies are needed to fully understand their role in the positivity bias and the potential for therapeutic interventions.</p>","PeriodicalId":9192,"journal":{"name":"Brain Imaging and Behavior","volume":null,"pages":null},"PeriodicalIF":2.4,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11222031/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139544978","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Victor Galvez, César Romero-Rebollar, M Anayali Estudillo-Guerra, Juan Fernandez-Ruiz
{"title":"Resting-state networks and their relationship with MoCA performance in PD patients.","authors":"Victor Galvez, César Romero-Rebollar, M Anayali Estudillo-Guerra, Juan Fernandez-Ruiz","doi":"10.1007/s11682-024-00860-3","DOIUrl":"10.1007/s11682-024-00860-3","url":null,"abstract":"<p><p>Although mild cognitive impairment is a common non-motor symptom experienced by individuals with Parkinson's Disease, the changes in intrinsic resting-state networks associated with its onset in Parkinson's remain underexamined. To address the issue, our study sought to examine resting-state network alterations and their association with total performance in the Montreal Cognitive Assessment and its cognitive domains in Parkinson's by means of functional magnetic resonance imaging of 29 Parkinson's patients with normal cognition, 25 Parkinson's patients with mild cognitive impairment, and 13 healthy controls. To contrast the Parkinson's groups with each other and the controls, the images were used to estimate the Z-score coefficient between the regions of interest from the default mode network, the salience network and the central executive network. Our first finding was that default mode and salience network connectivity decreased significantly in Parkinson's patients regardless of their cognitive status. Additionally, default mode network nodes had a negative and salience network nodes a positive correlation with the global assessment in Parkinson's with normal cognition; this inverse relationship of both networks to total score was not found in the group with cognitive impairment. Finally, a positive correlation was found between executive scores and anterior and posterior cortical network connectivity and, in the group with cognitive impairment, between language scores and salience network connectivity. Our results suggest that specific resting-state networks of Parkinson's patients with cognitive impairment differ from those of Parkinson's patients with normal cognition, supporting the evidence that cognitive impairment in Parkinson's Disease displays a differentiated neurodegenerative pattern.</p>","PeriodicalId":9192,"journal":{"name":"Brain Imaging and Behavior","volume":null,"pages":null},"PeriodicalIF":2.4,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139706110","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Meenu Ajith, Dawn M Aycock, Erin B Tone, Jingyu Liu, Maria B Misiura, Rebecca Ellis, Sergey M Plis, Tricia Z King, Vonetta M Dotson, Vince Calhoun
{"title":"A deep learning approach for mental health quality prediction using functional network connectivity and assessment data.","authors":"Meenu Ajith, Dawn M Aycock, Erin B Tone, Jingyu Liu, Maria B Misiura, Rebecca Ellis, Sergey M Plis, Tricia Z King, Vonetta M Dotson, Vince Calhoun","doi":"10.1007/s11682-024-00857-y","DOIUrl":"10.1007/s11682-024-00857-y","url":null,"abstract":"<p><p>While one can characterize mental health using questionnaires, such tools do not provide direct insight into the underlying biology. By linking approaches that visualize brain activity to questionnaires in the context of individualized prediction, we can gain new insights into the biology and behavioral aspects of brain health. Resting-state fMRI (rs-fMRI) can be used to identify biomarkers of these conditions and study patterns of abnormal connectivity. In this work, we estimate mental health quality for individual participants using static functional network connectivity (sFNC) data from rs-fMRI. The deep learning model uses the sFNC data as input to predict four categories of mental health quality and visualize the neural patterns indicative of each group. We used guided gradient class activation maps (guided Grad-CAM) to identify the most discriminative sFNC patterns. The effectiveness of this model was validated using the UK Biobank dataset, in which we showed that our approach outperformed four alternative models by 4-18% accuracy. The proposed model's performance evaluation yielded a classification accuracy of 76%, 78%, 88%, and 98% for the excellent, good, fair, and poor mental health categories, with poor mental health accuracy being the highest. The findings show distinct sFNC patterns across each group. The patterns associated with excellent mental health consist of the cerebellar-subcortical regions, whereas the most prominent areas in the poor mental health category are in the sensorimotor and visual domains. Thus the combination of rs-fMRI and deep learning opens a promising path for developing a comprehensive framework to evaluate and measure mental health. Moreover, this approach had the potential to guide the development of personalized interventions and enable the monitoring of treatment response. Overall this highlights the crucial role of advanced imaging modalities and deep learning algorithms in advancing our understanding and management of mental health.</p>","PeriodicalId":9192,"journal":{"name":"Brain Imaging and Behavior","volume":null,"pages":null},"PeriodicalIF":2.4,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139715854","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Uncovering brain functional connectivity disruption patterns of lung cancer-related pain.","authors":"Xiaotong Wei, Yong Lai, Xiaosong Lan, Yong Tan, Jing Zhang, Jiang Liu, Jiao Chen, Chengfang Wang, Xiaoyu Zhou, Yu Tang, Daihong Liu, Jiuquan Zhang","doi":"10.1007/s11682-023-00836-9","DOIUrl":"10.1007/s11682-023-00836-9","url":null,"abstract":"<p><p>Pain is a pervasive symptom in lung cancer patients during the onset of the disease. This study aims to investigate the connectivity disruption patterns of the whole-brain functional network in lung cancer patients with cancer pain (CP+). We constructed individual whole-brain, region of interest (ROI)-level functional connectivity (FC) networks for 50 CP+ patients, 34 lung cancer patients without pain-related complaints (CP-), and 31 matched healthy controls (HC). Then, a ROI-based FC analysis was used to determine the disruptions of FC among the three groups. The relationships between aberrant FCs and clinical parameters were also characterized. The ROI-based FC analysis demonstrated that hypo-connectivity was present both in CP+ and CP- patients compared to HC, which were particularly clustered in the somatomotor and ventral attention, frontoparietal control, and default mode modules. Notably, compared to CP- patients, CP+ patients had hyper-connectivity in several brain regions mainly distributed in the somatomotor and visual modules, suggesting these abnormal FC patterns may be significant for cancer pain. Moreover, CP+ patients also showed increased intramodular and intermodular connectivity strength of the functional network, which could be replicated in cancer stage IV and lung adenocarcinoma. Finally, abnormal FCs within the prefrontal cortex and somatomotor cortex were positively correlated with pain intensity and pain duration, respectively. These findings suggested that lung cancer patients with cancer pain had disrupted connectivity in the intrinsic brain functional network, which may be the underlying neuroimaging mechanisms.</p>","PeriodicalId":9192,"journal":{"name":"Brain Imaging and Behavior","volume":null,"pages":null},"PeriodicalIF":2.4,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139691240","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Brain white matter microstructural alterations in patients with systemic lupus erythematosus: an automated fiber quantification study.","authors":"Peng Zhang, Yanhong Feng, Tianye Xu, Yifan Li, Jianguo Xia, Hongxia Zhang, Zhongru Sun, Weizhong Tian, Ji Zhang","doi":"10.1007/s11682-024-00861-2","DOIUrl":"10.1007/s11682-024-00861-2","url":null,"abstract":"<p><p>This study aimed to identify damaged segments of brain white matter fiber tracts in patients with systemic lupus erythematosus (SLE) using diffusion tensor imaging (DTI)-based automated fiber quantification (AFQ), and analyze their relationship with cognitive impairment. Clinical and imaging data for 39 female patients with SLE and for 44 female healthy controls (HCs) were collected. AFQ was used to track whole-brain white matter tracts in each participant, and each tract was segmented into 100 equally spaced nodes. DTI metrics including fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD) were calculated at each node. Correlations were also explored between DTI metrics in the damaged segments of white matter fiber tracts and neuropsychological test scores of patients with SLE. Compared with HCs, SLE patients exhibited significantly lower FA values, and significantly higher MD, AD, RD values in many white matter tracts (all P < 0.05, false discovery rate-corrected). FA values in nodes 97-100 of the left inferior fronto-occipital fasciculus (IFOF) positively correlated with the mini-mental state examination score. AFQ enables precise and accurate identification of damage to white matter fiber tracts in brains of patients with SLE. FA values in the left IFOF correlate with cognitive impairment in SLE.</p>","PeriodicalId":9192,"journal":{"name":"Brain Imaging and Behavior","volume":null,"pages":null},"PeriodicalIF":2.4,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139706109","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Functional connectivity changes of the hippocampal subregions in anti-N-methyl-D-aspartate receptor encephalitis.","authors":"Yujie Yang, Shishun Fu, Guihua Jiang, Guang Xu, Junzhang Tian, Xiaofen Ma","doi":"10.1007/s11682-024-00852-3","DOIUrl":"10.1007/s11682-024-00852-3","url":null,"abstract":"<p><p>The hippocampus plays an important role in the pathophysiological mechanism of Anti-N-methyl-D-aspartate receptor (anti-NMDAR) encephalitis. Nevertheless, the connection between the resting-state activity of the hippocampal subregions and neuropsychiatric disorders in patients remains unclear. This study aimed to explore the changes in functional connectivity (FC) in the hippocampal subregions of patients with anti-NMDAR encephalitis and its association with clinical symptoms and cognitive performance. Twenty-three patients with anti-NMDAR encephalitis and 23 healthy controls (HC) were recruited. All participants underwent resting-state functional magnetic resonance imaging (rs-fMRI) scans and completed clinical cognitive scales. Based on the Brainnetome Atlas, the rostral (anterior) and caudal (posterior) hippocampi of both the left and right hemispheres were selected as regions of interest (ROIs) for FC analysis. First, a one-sample t-test was used to observe the whole-brain connectivity distribution of hippocampal subregions within the patient and HC groups at a threshold of p < 0.05. The two-sample t-test was used to compare the differences in hippocampal ROIs connectivity between groups, followed by a partial correlation analysis between the FC values of brain regions with statistical differences and clinical variables. This study observed that the distribution of whole-brain functional connectivity in the rostral and caudal hippocampi aligned with the connectivity differences between the anterior and posterior hippocampi. Compared to the HC group, the patients showed significantly decreased FC between the bilateral rostral hippocampus and the left inferior orbitofrontal gyrus and between the right rostral hippocampus and the right cerebellum. However, a significant increase in FC was observed between the right rostral hippocampus and left superior temporal gyrus, the left caudal hippocampus and right superior frontal gyrus, and the right caudal hippocampus and left gyrus rectus. Partial correlation analysis showed that FC between the left inferior orbitofrontal gyrus and the right rostral hippocampus was significantly negatively correlated with the California Verbal Learning Test (CVLT) and Brief Visuospatial Memory Test (BVMT) scores. The FC between the right rostral hippocampus and the left superior temporal gyrus was negatively correlated with BVMT scores. FC abnormalities in the hippocampal subregions of patients with anti-NMDAR encephalitis were associated with cognitive impairment, emotional changes, and seizures. These results may help explain the pathophysiological mechanisms and clinical manifestations of anti-NMDAR encephalitis and NMDAR dysfunction-related diseases such as schizophrenia.</p>","PeriodicalId":9192,"journal":{"name":"Brain Imaging and Behavior","volume":null,"pages":null},"PeriodicalIF":2.4,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139740444","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Sarah L Brassard, Hanson Liu, Jadyn Dosanjh, James MacKillop, Iris Balodis
{"title":"Neurobiological foundations and clinical relevance of effort-based decision-making.","authors":"Sarah L Brassard, Hanson Liu, Jadyn Dosanjh, James MacKillop, Iris Balodis","doi":"10.1007/s11682-024-00890-x","DOIUrl":"https://doi.org/10.1007/s11682-024-00890-x","url":null,"abstract":"<p><p>Applying effort-based decision-making tasks provides insights into specific variables influencing choice behaviors. The current review summarizes the structural and functional neuroanatomy of effort-based decision-making. Across 39 examined studies, the review highlights the ventromedial prefrontal cortex in forming reward-based predictions, the ventral striatum encoding expected subjective values driven by reward size, the dorsal anterior cingulate cortex for monitoring choices to maximize rewards, and specific motor areas preparing for effort expenditure. Neuromodulation techniques, along with shifting environmental and internal states, are promising novel treatment interventions for altering neural alterations underlying decision-making. Our review further articulates the translational promise of this construct into the development, maintenance and treatment of psychiatric conditions, particularly those characterized by reward-, effort- and valuation-related deficits.</p>","PeriodicalId":9192,"journal":{"name":"Brain Imaging and Behavior","volume":null,"pages":null},"PeriodicalIF":3.2,"publicationDate":"2024-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141178639","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Cross-sectional and longitudinal evaluation of white matter microstructure damage and cognitive correlations by automated fibre quantification in relapsing-remitting multiple sclerosis patients.","authors":"Zichun Yan, Zeyun Tan, Qiyuan Zhu, Zhuowei Shi, Jinzhou Feng, Yiqiu Wei, Feiyue Yin, Xiaohua Wang, Yongmei Li","doi":"10.1007/s11682-024-00893-8","DOIUrl":"https://doi.org/10.1007/s11682-024-00893-8","url":null,"abstract":"<p><p>The purpose of this study was to characterize whole-brain white matter (WM) fibre tracts by automated fibre quantification (AFQ), capture subtle changes cross-sectionally and longitudinally in relapsing-remitting multiple sclerosis (RRMS) patients and explore correlations between these changes and cognitive performance A total of 114 RRMS patients and 71 healthy controls (HCs) were enrolled and follow-up investigations were conducted on 46 RRMS patients. Fractional anisotropy (FA), mean diffusion (MD), axial diffusivity (AD), and radial diffusivity (RD) at each node along the 20 WM fibre tracts identified by AFQ were investigated cross-sectionally and longitudinally in entire and pointwise manners. Partial correlation analyses were performed between the abnormal metrics and cognitive performance. At baseline, compared with HCs, patients with RRMS showed a widespread decrease in FA and increases in MD, AD, and RD among tracts. In the pointwise comparisons, more detailed abnormalities were localized to specific positions. At follow-up, although there was no significant difference in the entire WM fibre tract, there was a reduction in FA in the posterior portion of the right superior longitudinal fasciculus (R_SLF) and elevations in MD and AD in the anterior and posterior portions of the right arcuate fasciculus (R_AF) in the pointwise analysis. Furthermore, the altered metrics were widely correlated with cognitive performance in RRMS patients. RRMS patients exhibited widespread WM microstructure alterations at baseline and alterations in certain regions at follow-up, and the altered metrics were widely correlated with cognitive performance in RRMS patients, which will enhance our understanding of WM microstructure damage and its cognitive correlation in RRMS patients.</p>","PeriodicalId":9192,"journal":{"name":"Brain Imaging and Behavior","volume":null,"pages":null},"PeriodicalIF":3.2,"publicationDate":"2024-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141173730","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Abnormal brain functional network dynamics in amyotrophic lateral sclerosis patients with depression.","authors":"Sujuan Sun, Yujing Chen, Bing Zhao, Jun Zhu, Tianrui Wen, Bingnan Peng, Qingguo Ren, Xiaohan Sun, Pengfei Lin, Dong Zhang, Shuangwu Liu","doi":"10.1007/s11682-024-00896-5","DOIUrl":"https://doi.org/10.1007/s11682-024-00896-5","url":null,"abstract":"<p><p>Since depression is common in amyotrophic lateral sclerosis (ALS) patients, we aimed to explore the specific brain functional network dynamics in ALS patients with depression (ALS-D) compared with healthy controls (HCs) and ALS patients without depressive symptoms (ALS-ND). According to the DSM-V, 32 ALS-D patients were selected from a large and newly diagnosed ALS cohort. Then, 32 demographic- and cognitive-matched ALS-ND patients were also selected, and 64 HCs were recruited. These participants underwent resting-state fMRI scans, and functional connectivity state analysis and dynamic graph theory were applied to evaluate brain functional network dynamics. Moreover, the Hamilton Depression Rating Scale (HDRS) was used to quantify depressive symptoms in the ALS-D patients. Four distinct states were identified in the ALS-D patients and controls. Compared with that in HCs, the fraction rate (FR) in state 2 was significantly decreased in ALS-D patients, and the FR in state 4 was significantly increased in ALS-D patients. Compared with that of HCs, the dwell time in state 4 was significantly increased in the ALS-D patients. Moreover, compared with that in the ALS-D patients, the FR in state 3 was significantly decreased in the ALS-ND patients. Among the ALS-D patients, there was the suggestion of a positive association between HDRS scores and dwell time of state 4, but this association did not reach statistical significance (r = 0.354; p = 0.055). Depression is an important feature of ALS patients, and we found a special pattern of brain functional network dynamics in ALS-D patients. Our findings may play an important role in understanding the mechanism underlying depression in ALS patients and help develop therapeutic interventions for depressed ALS patients.</p>","PeriodicalId":9192,"journal":{"name":"Brain Imaging and Behavior","volume":null,"pages":null},"PeriodicalIF":3.2,"publicationDate":"2024-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141173791","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}