White matter damage in multiple sclerosis disproportionately targets default mode, executive control, and salience networks.

Late-life cognitive impairment and depression frequently co-occur and share many symptoms. However, the specific neural and clinical factors contributing to both their common and distinct profiles in older adults remain unclear. We investigated resting-state correlates of cognitive and depressive symptoms in older adults (n=248 and n=95) using clinical, blood, and neuroimaging data. We computed a connectivity matrix across default mode, executive control, and salience networks. Cross-validated elastic net regression identified features reflecting cognitive function and depressive symptoms. These features were validated on a held-out dataset. We discovered that white matter hyperintensities and nine overlapping nodes spanning all three networks are associated with both cognitive function and depressive symptoms, including left amygdala, left hippocampus, and bilateral ventral tegmental area. Our findings reveal intertwined neural nodes influencing cognitive impairment and depressive symptoms in late life, offering insights into shared characteristics and potential therapeutic targets. Resting-state neuroimaging markers are associated with symptoms of cognitive decline and late-life depression. Symptom-associated connectivity alterations were present across three major brain networks of interest, including the salience, default mode, and executive control networks. Some regions of interest are associated with both cognitive function and depressive symptoms, including the left amygdala, left hippocampus, and bilateral ventral tegmental area.

BackgroundInflammatory processes play a pivotal role in the degenerative process of Alzheimer’s disease. In humans, a biallelic (C/T) polymorphism in the promoter region (position-511) (rs16944) of the interleukin-1 beta gene has been significantly associated with differences in the secretory capacity of interleukin-1 beta. In this study, we investigated whether this functional polymorphism mediates the brain networks in patients with Alzheimer’s disease.MethodsWe enrolled a total of 135 patients with Alzheimer’s disease (65 males, 70 females), and investigated their gray matter structural covariance networks using 3D T1 magnetic resonance imaging and their white matter macro-structural integrities using fractional anisotropy. The patients were classified into two genotype groups: C-carriers (n = 108) and TT-carriers (n = 27), and the structural covariance networks were constructed using seed-based analysis focusing on the default mode network medial temporal or dorsal medial subsystem, salience network and executive control network. Neurobehavioral scores were used as the major outcome factors for clinical correlations.ResultsThere were no differences between the two genotype groups in the cognitive test scores, seed, or peak cluster volumes and white matter fractional anisotropy. The covariance strength showing C-carriers > TT-carriers was the entorhinal-cingulum axis. There were two peak clusters (Brodmann 6 and 10) in the salience network and four peak clusters (superior prefrontal, precentral, fusiform, and temporal) in the executive control network that showed C-carriers < TT-carriers in covariance strength. The salience network and executive control network peak clusters in the TT group and the default mode network peak clusters in the C-carriers strongly predicted the cognitive test scores.ConclusionsInterleukin-1 beta C-511 T polymorphism modulates the structural covariance strength on the anterior brain network and entorhinal-interconnected network which were independent of the white matter tract integrity. Depending on the specific C-511 T genotype, different network clusters could predict the cognitive tests.

Background: Chronic insomnia (CID) is a highly prevalent sleep disorder, yet the precise mechanisms underlying it remain incompletely understood. The aim of this study is to analyze effective connectivity between key regions of the default mode network (DMN), executive control network (ECN), and salience network (SN) in patients with CID as potential neurologic correlates of the hyperarousal state. Methods: Thirty-one CID patients and 24 healthy controls (HC) were recruited. All the subjects filled out the Insomnia severity index scale (ISI), Beck depression inventory (BDI), and Epworth sleepiness scale (ESS), underwent polysomnography, and were scanned on functional magnetic resonance imaging. Statistical Parametric Mapping 12 was used to analyze the results. Spectral dynamic causal modeling was applied to the chosen regions of interest. Results: There were three significant connections present in the CID group-inhibitory from the dorsolateral prefrontal cortex (DLPFC) to the right hippocampus (Hippocamp R); excitatory from the dorsomedial prefrontal cortex to the ventromedial prefrontal cortex; and excitatory from the common medial prefrontal cortex to the right anterior insula (AIR). Two statistically significant excitatory connections were lacking in the patients' group-from the posterior cingulate cortex (PCC) to AIR, and from precuneus to PCC. CID patients scored higher on the ISI and BDI. Significant negative correlations between DLPFC-Hippocamp R connectivity and both ISI and BDI scores were identified. Conclusions: Disruptions within the DMN and between the DMN, SN, and ECN reflect an impaired ability to appropriately shift between internally and externally directed cognitive states-an imbalance that potentially underlies the hyperarousal state of CID.

IntroductionReward processing is a key aspect of cognitive control processes, putatively instantiated by mesolimbic and mesocortical brain circuits. Deficient signaling within these circuits has been associated with psychopathology. We applied a network discovery approach to assess specific functional networks associated with reward processing in participants with attention-deficit/hyperactivity disorder (ADHD).MethodsTo describe task-related processes in terms of integrated functional networks, we applied independent component analysis (ICA) to task response maps of 60 healthy participants who performed a monetary incentive delay (MID) task. The resulting components were interpreted on the basis of their similarity with group-level task responses as well as their similarity with brain networks derived from resting state fMRI analyses. ADHD-related effects on network characteristics including functional connectivity and communication between networks were examined in an independent sample comprising 150 participants with ADHD and 48 healthy controls.ResultsWe identified 23 components to be associated with 4 large-scale functional networks: the default-mode, visual, executive control, and salience networks. The salience network showed a specific association with reward processing as well as the highest degree of within-network integration. ADHD was associated with decreased functional connectivity between the salience and executive control networks as well as with peripheral brain regions.ConclusionsReward processing as measured with the MID task involves one reward-specific and three general functional networks. Participants with ADHD exhibited alterations in connectivity of both the salience and executive control networks and associated brain regions during task performance.

Similarities and differences in dynamic properties of brain networks between internet gaming disorder and tobacco use disorder

Creative constraints: Brain activity and network dynamics underlying semantic interference during idea production

Decline in cognitive skills, especially in memory, is often viewed as part of "normal" aging. Yet some individuals "age better" than others. Building on prior research showing that cortical thickness in one brain region, the anterior midcingulate cortex, is preserved in older adults with memory performance abilities equal to or better than those of people 20-30 years younger (i.e., "superagers"), we examined the structural integrity of two large-scale intrinsic brain networks in superaging: the default mode network, typically engaged during memory encoding and retrieval tasks, and the salience network, typically engaged during attention, motivation, and executive function tasks. We predicted that superagers would have preserved cortical thickness in critical nodes in these networks. We defined superagers (60-80 years old) based on their performance compared to young adults (18-32 years old) on the California Verbal Learning Test Long Delay Free Recall test. We found regions within the networks of interest where the cerebral cortex of superagers was thicker than that of typical older adults, and where superagers were anatomically indistinguishable from young adults; hippocampal volume was also preserved in superagers. Within the full group of older adults, thickness of a number of regions, including the anterior temporal cortex, rostral medial prefrontal cortex, and anterior midcingulate cortex, correlated with memory performance, as did the volume of the hippocampus. These results indicate older adults with youthful memory abilities have youthful brain regions in key paralimbic and limbic nodes of the default mode and salience networks that support attentional, executive, and mnemonic processes subserving memory function. Memory performance typically declines with age, as does cortical structural integrity, yet some older adults maintain youthful memory. We tested the hypothesis that superagers (older individuals with youthful memory performance) would exhibit preserved neuroanatomy in key brain networks subserving memory. We found that superagers not only perform similarly to young adults on memory testing, they also do not show the typical patterns of brain atrophy in certain regions. These regions are contained largely within two major intrinsic brain networks: the default mode network, implicated in memory encoding, storage, and retrieval, and the salience network, associated with attention and executive processes involved in encoding and retrieval. Preserved neuroanatomical integrity in these networks is associated with better memory performance among older adults.

Evolving brain network dynamics in early childhood: Insights from modular graph metrics

Nicotine replacement in abstinent smokers improves cognitive withdrawal symptoms with modulation of resting brain network dynamics

Brain tumors are a leading cause of disability and death among children. Brain tumor treatments are often required for cure, but are damaging to brain tissue – particularly white matter, and is related to cognitive impairments for pediatric brain tumor survivors (PBTS). White matter tracts are critical for neural communication and supports cognition, including information processing speed, which underlies higher-order cognitive processes and is mediated by the brain’s default mode (DMN) and executive control (ECN) networks. It is unknown how white matter damage results in compromised information processing speed in PBTS. Thus, we explore the impact of DMN and ECN structural and functional connectivity on cognition during resting state, a visual-motor task, and through computational modeling. Forty-one healthy children and fifty-two PBTS were scanned at The Hospital for Sick Children. Tractography was conducted to examine DMN and ECN structural connectivity. MEG and measures of neural communication was conducted to examine DMN and ECN functional connectivity. Computational models were built using experimentally acquired structural connectomes to simulate functional connectivity. Partial least-squares path modeling was conducted to describe the relationship among white matter organization, neural communication, and information processing speed. Compared to healthy children, PBTS showed: slower information processing speed, DMN and ECN white matter compromise, and resting state DMN and ECN neural communication compromise that generalized to simulated and task-based neural synchrony compromise. Overall, DMN and ECN structural connectivity significantly influenced network neural communication and information processing speed, and white matter compromise had an indirect adverse impact on reaction time via perturbed neural synchrony. Our findings show an important connection between DMN and ECN connectivity that is essential for information processing speed. Further establishing alterations in DMN and ECN structural and functional connectivity as novel biomarkers of cognitive impairments could facilitate early intervention and monitoring of these deficits following brain tumor treatment. Citation Format: Noor Al Dahhan. Mechanisms of Cognitive Impairment in Children Treated for Brain Tumors [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Brain Cancer; 2026 Mar 23-25; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2026;86(6_Suppl):Abstract nr PR006.

Altered coupling of default-mode, executive-control and salience networks in Internet gaming disorder

Traumatic brain injury (TBI) and stroke are the most common causes of acquired brain injury (ABI), annually affecting 69 million and 15 million people, respectively. Following ABI, the relationship between brain network disruption and common cognitive issues including attention dysfunction is heterogenous. Using PRISMA guidelines, we systematically reviewed 43 studies published by February 2023 that reported correlations between attention and connectivity. Across all ages and stages of recovery, following TBI, greater attention was associated with greater structural efficiency within/between executive control network (ECN), salience network (SN), and default mode network (DMN) and greater functional connectivity (fc) within/between ECN and DMN, indicating DMN interference. Following stroke, greater attention was associated with greater structural connectivity (sc) within ECN; or greater fc within the dorsal attention network (DAN). In childhood ABI populations, decreases in structural network segregation were associated with greater attention. Longitudinal recovery from TBI was associated with normalization of DMN activity, and in stroke, normalization of DMN and DAN activity. Results improve clinical understanding of attention-related connectivity changes after ABI. Recommendations for future research include increased use of electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) to measure connectivity at the point of care, standardized attention and connectivity outcome measures and analysis pipelines, detailed reporting of patient symptomatology, and casual analysis of attention-related connectivity using brain stimulation.

Symptom heterogeneity characterizes psychotic disorders and hinders the delineation of underlying biomarkers. Here, we identify symptom-based subtypes of recent-onset psychosis (ROP) patients from the multi-center PRONIA (Personalized Prognostic Tools for Early Psychosis Management) database and explore their multimodal biological and functional signatures. We clustered N = 328 ROP patients based on their maximum factor scores in an exploratory factor analysis on the Positive and Negative Syndrome Scale items. We assessed inter-subgroup differences and compared to N = 464 healthy control (HC) individuals regarding gray matter volume (GMV), neurocognition, polygenic risk scores, and longitudinal functioning trajectories. Finally, we evaluated factor stability at 9- and 18-month follow-ups. A 4-factor solution optimally explained symptom heterogeneity, showing moderate longitudinal stability. The ROP-MOTCOG (Motor/Cognition) subgroup was characterized by GMV reductions within salience, control and default mode networks, predominantly throughout cingulate regions, relative to HC individuals, had the most impaired neurocognition and the highest genetic liability for schizophrenia. ROP-SOCWD (Social Withdrawal) patients showed GMV reductions within medial fronto-temporal regions of the control, default mode, and salience networks, and had the lowest social functioning across time points. ROP-POS (Positive) evidenced GMV decreases in salience, limbic and frontal regions of the control and default mode networks. The ROP-AFF (Affective) subgroup showed GMV reductions in the salience, limbic, and posterior default-mode and control networks, thalamus and cerebellum. GMV reductions in fronto-temporal regions of the salience and control networks were shared across subgroups. Our results highlight the existence of behavioral subgroups with distinct neurobiological and functional profiles in early psychosis, emphasizing the need for refined symptom-based diagnosis and prognosis frameworks.

BackgroundInternal capsule strokes often result in multidomain cognitive impairments across memory, attention, and executive function, typically due to disruptions in brain network connectivity. Our study examines these impairments by analyzing interactions within the triple-network model, focusing on both static and dynamic aspects. MethodsWe collected resting-state fMRI data from 62 left (CI_L) and 56 right (CI_R) internal capsule stroke patients, along with 57 healthy controls (HC). Using independent component analysis to extract the default mode (DMN), executive control (ECN), and salience networks (SAN), we conducted static and dynamic functional network connectivity analyses (DFNC) to identify differences between stroke patients and controls. For DFNC, we used k-means clustering to focus on temporal properties and multilayer network analysis to examine integration and modularity Q, where integration represents dynamic interactions between networks, and modularity Q measures how well the network is divided into distinct modules. We then calculated the correlations between SFNC/DFNC properties with significant inter-group differences and cognitive scales. ResultsCompared to HC, both CI_L and CI_R patients showed increased static FCs between SAN and DMN and decreased dynamic interactions between ECN and other networks. CI_R patients also had heightened static FCs between SAN and ECN and maintained a state with strongly positive FNCs across all networks in the triple-network model. Additionally, CI_R patients displayed decreased modularity Q. ConclusionThese findings highlight that stroke can result in the disruption of static and dynamic interactions in the triple network model, aiding our understanding of the neuropathological basis for multidomain cognitive deficits after internal capsule stroke.

目的 探讨精神分裂症患者脑静息态默认网络、中心执行网络及突显网络的网络内及网络间的功能连接特点.方法 对74例精神分裂症患者(患者组)和79名相匹配的健康者(对照组)进行静息态fMRI扫描.采取功能连接分析方法,以内侧前额叶皮质及右侧前岛叶为感兴趣区域分别提取默认网络、中心执行网络及突显网络,分析3个网络内及网络间静息态功能连接情况;并对有差异的功能连接与精神症状及病程等进行偏相关分析.结果 与对照组相比,患者组内侧前额叶皮质与双侧背外侧前额叶皮质(左侧-0.02±0.18与-0.12±0.12,t=4.25,P＜0.01;右侧-0.02±0.11与-0.10±0.10,t=5.40,P＜0.01)、双侧豆状壳核(左侧0.14±0.12与0.04±0.10,t=5.03,P＜0.01;右侧0.13±0.11与0.03±0.98,t=4.96,P＜0.01)的功能连接增强;右侧前岛叶与左侧额中回(-0.05±0.17与-0.07±0.17,t=4.60,P＜0.01)及楔前叶/后扣带回(0.01±0.13与-0.09±0.14,t=4.01,P＜0.01)的功能连接增强(均采用高斯随机场理论校正,体素水平P＜0.01,簇水平P＜0.05);默认网络与中心执行网络、突显网络间的负向功能连接减小甚至消失(Bonferroni校正P＜0.05).患者组PANSS阳性症状分与右侧前岛叶与楔前叶/后扣带回皮质间的功能连接呈正相关(r=0.232,P=0.025);患者组病程与右侧前岛叶与左侧额中回(r=0.288,P=0.007)、楔前叶/后扣带回(r=0.196,P=0.049)间的功能连接呈正相关.结论 精神分裂症患者存在静息态默认网络、中心执行网络及突显网络3个网络间的连接异常,可能与精神分裂症的病理机制有关.