Salience Network Connectivity Research Articles

Disease-specific alterations of effective connectivity across anti-correlated networks in major depressive disorder and bipolar disorder.

Major depressive disorder (MDD) and bipolar disorder (BD) share various clinical behaviors and have confounded clinical diagnoses. Converging studies have suggested MDD and BD as disorders with abnormal communication among functional brain networks involved in mental activity and redirection. However, whether MDD and BD show disease-specific alterations in network information interaction remains unclear. This study collected resting-state functional MRI data of 98 patients with MDD, 55 patients with BD, and sex-, age-, and education-matched 95 healthy controls. Spectral dynamic causal model (spDCM) was used to investigate effective connectivities among three large-scale intrinsic functional networks including the default mode network (DMN), salience network (SN), and dorsal attention network (DAN). Effective connectivities showing disease-specific changes were then used as input features of support vector models to predict clinical symptoms and classify individuals with MDD and BD. Compared with healthy controls, both the MDD and BD groups showed increased DAN → SN connectivity. However, within-network connectivities of DMN and DAN showed opposite effects on the diseases. Notably, MDD and BD also showed different alterations on a connectivity loop of SN → DAN → DMN → SN, which could be used to predict the clinical symptom severity of either MDD or BD. Individuals with MDD and BD could be further classified by using connectivities showing opposite disease effects. Our findings reveal common and unique alterations of network interactions in MDD and BD, and further suggest disease-specific neuroimaging markers for clinical diagnosis.

Resting state EEG source derived salience network theta connectivity mediates anxiety in community dwelling individuals reporting childhood trauma.

Childhood trauma (CT) has been consistently linked with etiology of anxiety and depression. Finding biomarkers that mediate the relationship between CT and psychopathology is important and electroencephalography (EEG) can be a useful and cost-effective tool serving this purpose. Hence, in the current research we investigated resting state EEG biomarkers associated with CT and how these may link to psychopathology of anxiety and depression in adults. A total of 324 community recruited participants (age range 15-93 years) completed standard self-report scales of CT, anxiety and depression, and also underwent an eyes-closed resting state EEG recording session. Based on several functional neuroimaging studies, which have shown that connectivity in the salience network with major nodes in the anterior cingulate cortex (ACC) and insula is modulated by CT, we derived salience network connectivity measures from resting state EEG source imaging. Also given that theta band (3-7 Hz) neural oscillations have been shown to have an ACC source, we specifically focused on theta band salience network connectivity. The results showed significant positive correlation between CT and both anxiety and depression. We also found that theta band salience network connectivity, but not network activity, had a significant inverse relationship with CT and specifically mediated the relationship between CT and anxiety, but not depression. Interrogating the subcomponents of CT, theta connectivity in the salience network mediated the relationship between anxiety and both emotional abuse and physical neglect. These results showcase the utility of a resting state EEG source imaging-based biomarker in understanding the mechanistic associations between CT and psychopathology in community dwelling individuals.

"Expectancy-Mood Neural Dynamics Predict Mechanisms of Short- and Long-Term Antidepressant Placebo Effects".

Acute experimental models of antidepressant placebo effects suggest that expectancies, encoded within the salience network (SN), are reinforced by sensory evidence and mood fluctuations. However, whether these dynamics extend to longer timescales remains unknown. To answer this question, we investigated how SN and default mode network (DMN) functional connectivity during the processing of antidepressant expectancies facilitates the shift from salience attribution to contextual cues in the SN to belief-induced mood responses in the DMN, both acutely and long-term. Sixty psychotropic-free patients with major depressive disorder (MDD) completed an acute antidepressant placebo fMRI experiment manipulating placebo-associated expectancies and their reinforcement while assessing trial-by-trial mood improvement, before entering an 8-week double-blind, randomized, placebo-controlled trial (RCT) of a selective serotonin reuptake inhibitor (SSRI) or placebo. Learned antidepressant expectancies predicted by a reinforcement learning model modulated SN-DMN connectivity. Acutely, greater modulation predicted higher effects of expectancy and reinforcement manipulations on reported expectancies and mood. Over 8 weeks, no significant drug effects on mood improvement were observed. However, participants who believed they were receiving an antidepressant exhibited significantly greater mood improvement, irrespective of the actual treatment received. Moreover, increased SN-DMN connectivity predicted mood improvement, especially in placebo-treated participants who believed they received an SSRI. SN-DMN interactions may play a critical role in the evolution of antidepressant response expectancies, drug-assignment beliefs, and their effects on mood.

Functional connectivity profiles in remitted depression and their relation to ruminative thinking

The triple network model suggests that dysfunction in three major brain networks – the default mode network (DMN), central executive network (CEN), and salience network (SN) – might contribute to cognitive impairments in various psychiatric disorders, including major depressive disorder (MDD). While hyperconnectivity in the DMN, hypoconnectivity in the CEN, and abnormal SN connectivity have been observed in acutely depressed patients, evidence for network alterations during remission is limited. Further, there are few studies examining connectivity in people in remission from MDD (rMDD) during emotional processing tasks, including during affective cognition (i.e., tasks that encompass affective processing in the context of cognitive processes, such as inhibition).To address these literature gaps, this study compared functional connectivity (FC) between resting and task conditions, specifically during the emotional Stroop (eStroop) task, as well as between rMDD and healthy volunteers (HVs), within and between nodes of the three networks. We also explored how FC relates to rumination in the rMDD group, given that rumination tends to persist in rMDD and involves affective and cognitive networks.We unexpectedly found greater FC during the task vs. rest condition within the DMN, and decreased FC during the task vs. rest conditions within the CEN and SN across the groups. Greater FC during the task vs. rest condition between DMN and SN nodes, as well as between CEN and SN nodes were also observed. These effects were more pronounced in the rMDD group as per our exploratory analyses. Additionally, the rMDD vs. HV group showed higher FC between DMN-CEN nodes, regardless of condition. Higher hopeless rumination scores were associated with decreased resting FC within the DMN, while higher active problem-solving scores were associated with increased task FC within the DMN in the rMDD group.These findings suggest that tasks engaging affective cognition processes influence FC within and among the three networks, with this effect more pronounced in the rMDD group. This might indicate potential protective and compensatory mechanisms in rMDD and expands our understanding of large-scale intrinsic network connectivity alterations during remission from depression. However, given the limited sample and the exploratory nature of some of our analyses, replication is necessary.

Multi-omics insights into the microbiota-gut-brain axis and cognitive improvement post-bariatric surgery

BackgroundAlthough numerous studies have shown that bariatric surgery results in sustained weight loss and modifications in gut microbiota composition and cognitive function, the exact underlying mechanisms are unclear. This study aimed to investigate the effects of bariatric surgery on cognitive function through the microbiota-gut-brain axis (MGBA).MethodsDemographic data, serum samples, fecal samples, cognitive assessment scales, and resting-state functional connectivity magnetic resonance imaging (rs-fMRI) scans were obtained from 39 obese patients before and after (6 months) laparoscopic sleeve gastrectomy (LSG). PCA analysis, OPLS-DA analysis, and permutation tests were used to conduct fecal 16 S microbiota profiling, serum metabolomics, and neuroimaging analyses, and a bariatric surgery-specific rs-fMRI brain functional connectivity network was constructed. Spearman correlation analysis and Co-inertia analysis were employed to correlate significant alterations in cognitive assessment scales and resting-state functional connectivity difference networks with differential serum metabolites and 16 S microbiota data to identify key gut microbiota and serum metabolic factors.ResultsLSG significantly reduced the weight of obese patients, with reductions of up to 28%. Furthermore, cognitive assessment scale measurements revealed that LSG enhanced cognitive functions, including memory (HVLT, p = 0.000) and executive function (SCWT, p = 0.008). Also, LSG significantly altered gut microbiota composition (p = 0.001), with increased microbial abundance and diversity (p < 0.05). Moreover, serum metabolite levels were significantly altered, revealing intergroup differences in 229 metabolites mapped to 72 metabolic pathways (p < 0.05, VIP > 1). Spearman correlation analysis among cognitive assessment scales, gut microbiota species, and serum metabolites revealed correlations with 68 gut microbiota species and 138 serum metabolites (p < 0.05). Furthermore, pairwise correlations were detected between gut microbiota and serum metabolites (p < 0.05). Functional neuroimaging analysis revealed that LSG increased functional connectivity in cognitive-related frontotemporal networks (FPN, p < 0.01). Additionally, normalization of the default mode network (DMN) and salience network (SN) connectivity was observed after LSG (p < 0.001). Further canonical correlation and correlation analysis suggested that the cognitive-related brain network changes induced by LSG were associated with key gut microbiota species (Akkermansia, Blautia, Collinsella, Phascolarctobacterium, and Ruminococcus, p < 0.05) and neuroactive metabolites (Glycine, L-Serine, DL-Dopa, SM (d18:1/24:1(15Z), p < 0.05).ConclusionThese findings indicate the pathophysiological role of the microbiota-gut-brain axis in enhancing cognitive function after bariatric surgery, and the study provides a basis for clinical dietary adjustments, probiotic supplementation, and guidance for bariatric surgery, but further research is still needed.Trial registrationChinese Clinical Trial Registry, ChiCTR2100049403. Registered 02 August 2021, https://www.chictr.org.cn/.

Decoding ruminative reflection in healthy individuals: The role of triple network connectivity

Ruminative reflection has been linked to enhanced executive control in processing internally represented emotional information, suggesting it may serve as an adaptive strategy for emotion regulation. Investigating the neural substrates of reflection can deepen our understanding of its adaptive properties. This study used network-based statistic (NBS)-Predict methodology to identify resting state functional connectivity (FC)-based predictors of ruminative reflection in a healthy sample. Our results showed that reflection in healthy subjects was predicted by FC within and between the default mode network (DMN), fronto-parietal network (FPN), and salience network (SN). Notably, FC within the FPN and SN, as well as between the FPN and DMN, contributed more significantly to the predictive model. These results underscore the greater influence of FPN and SN connectivity in predicting reflection, providing empirical evidence that increased executive control over internal emotional representations is integral to adaptive reflective processes. Moreover, the triple-network model, particularly the FPN-DMN coupling, emerges as a crucial predictor of ruminative reflection, highlighting the importance of coordinating self-relevant and goal-directed processing in reflective mechanisms. These identified connectivity fingerprints may offer insights into the role of reflective processes in facilitating recovery from depression.

Resting-state alterations in emotion salience and default-mode network connectivity in atypical trajectories of psychotic-like experiences.

Social cognition is commonly altered in people with psychosis. Two main brain networks have been implicated: the default-mode network (DMN), which is associated with socio-cognitive processing, and the salience network (SN) associated with socio-affective processing. Disturbances to the resting-state functional connectivity of these networks have been identified in schizophrenia and high-risk individuals, but there have been no studies in adolescents displaying distinct trajectories of subclinical psychotic-like experiences (PLEs). To address this, the present study measured SN and DMN resting-state connectivity in a unique longitudinally followed sample of youth (n = 92) presenting with typical and atypical 4-year PLE trajectories. Compared to the typically developing low PLE control group, the atypical increasing PLE trajectory displayed reduced connectivity between the SN and DMN, increased connectivity between left and right insula, and widespread dysconnectivity from the insula and amygdala. These alterations are similar to those reported in schizophrenia and clinical high-risk samples, suggesting that early detection may be useful for mapping the developmental trajectories of psychotic disorders.

The Contribution of Cognitive Control Networks in Word Selection Processing in Parkinson's Disease: Novel Insights from a Functional Connectivity Study.

Parkinson's disease (PD) patients are impaired in word production when the word has to be selected among competing alternatives requiring higher attentional resources. In PD, word selection processes are correlated with the structural integrity of the inferior frontal gyrus, which is critical for response selection, and the uncinate fasciculus, which is necessary for processing lexical information. In early PD, we investigated the role of the main cognitive large-scale networks, namely the salience network (SN), the central executive networks (CENs), and the default mode network (DMN), in word selection. Eighteen PD patients and sixteen healthy controls were required to derive nouns from verbs or generate verbs from nouns. Participants also underwent a resting-state functional MRI. Functional connectivity (FC) was examined using independent component analysis. Functional seeds for the SN, CENs, and DMN were defined as spheres, centered at the local activation maximum. Correlations were calculated between the FC of each functional seed and word production. A significant association between SN connectivity and task performance and, with less evidence, between CEN connectivity and the task requiring selection among a larger number of competitors, emerged in the PD group. These findings suggest the involvement of the SN and CEN in word selection in early PD, supporting the hypothesis of impaired executive control.

Effects of mini-basketball training program on social communication impairments and salience network in preschool children with autism spectrum disorder

Objectives This study aims to explore the impact of a 12-week mini-basketball training program (MBTP) on social communication impairments and salience network in preschool children with autism spectrum disorder (ASD), and to reveal the potential neural mechanisms by which MBTP improves social communication impairments in ASD children. Methods 34 ASD children aged 3–6 were assigned to the experimental group (n = 19) or the control group (n = 15). The experimental group received MBTP for 12 wk, while the control group received routine behavioral rehabilitation interventions from institutions. Social communication impairments in preschool ASD children is measured with the Social Response Scale Second Edition (SRS-2). Functional connectivity of salience network before and after testing is evaluated by resting-state functional magnetic resonance imaging (rs-fMRI). Results This study suggests improvement in the social cognitive dimension of preschool ASD children with the aid of MBTP as well as optimization of the functional connectivity of ASD children’s salience network. The potential neural mechanism of MBTP in improving social cognitive dimension in ASD children involved changes in functional connectivity in the left middle frontal gyrus and left thalamus. Conclusions This study infers that the MBTP may not improve the social communication impairments of the ASD children while it is likely to improve social cognitive aspect of social communication impairments and reduce the maladaptive traits of ASD children. Under this circumstance, the study could provide new evidence to explore the neural mechanisms of physical exercise improving social communication impairments and new targets for developing exercise intervention programs to improve social communication impairments in ASD children.

Cognitive and Salience Network Connectivity Changes following a Single Season of Repetitive Head Impact Exposure in High School Football.

During a season of high school football, adolescents with actively developing brains experience a considerable number of head impacts. Our aim was to determine whether repetitive head impacts in the absence of a clinically diagnosed concussion during a season of high school football produce changes in cognitive performance or functional connectivity of the salience network and its central hub, the dorsal anterior cingulate cortex. Football players were instrumented with the Head Impact Telemetry System during all practices and games, and the helmet sensor data were used to compute a risk-weighted exposure metric (RWEcp), accounting for the cumulative risk during the season. Participants underwent MRI and a cognitive battery (ImPACT) before and shortly after the football season. A control group of noncontact/limited-contact-sport athletes was formed from 2 cohorts: one from the same school and protocol and another from a separate, nearly identical study. Sixty-three football players and 34 control athletes were included in the cognitive performance analysis. Preseason, the control group scored significantly higher on the ImPACT Visual Motor (P = .04) and Reaction Time composites (P = .006). These differences increased postseason (P = .003, P < .001, respectively). Additionally, the control group had significantly higher postseason scores on the Visual Memory composite (P = .001). Compared with controls, football players showed significantly less improvement in the Verbal (P = .04) and Visual Memory composites (P = .01). A significantly greater percentage of contact athletes had lower-than-expected scores on the Verbal Memory (27% versus 6%), Visual Motor (21% versus 3%), and Reaction Time composites (24% versus 6%). Among football players, a higher RWEcp was significantly associated with greater increments in ImPACT Reaction Time (P = .03) and Total Symptom Scores postseason (P = .006). Fifty-seven football players and 13 control athletes were included in the imaging analyses. Postseason, football players showed significant decreases in interhemispheric connectivity of the dorsal anterior cingulate cortex (P = .026) and within-network connectivity of the salience network (P = .018). These decreases in dorsal anterior cingulate cortex interhemispheric connectivity and within-network connectivity of the salience network were significantly correlated with deteriorating ImPACT Total Symptom (P = .03) and Verbal Memory scores (P = .04). Head impact exposure during a single season of high school football is negatively associated with cognitive performance and brain network connectivity. Future studies should further characterize these short-term effects and examine their relationship with long-term sequelae.

Frontoparietal and salience network synchronizations during nonsymbolic magnitude processing predict brain age and mathematical performance in youth.

The development and refinement of functional brain circuits crucial to human cognition is a continuous process that spans from childhood to adulthood. Research increasingly focuses on mapping these evolving configurations, with the aim to identify markers for functional impairments and atypical development. Among human cognitive systems, nonsymbolic magnitude representations serve as a foundational building block for future success in mathematical learning and achievement for individuals. Using task-based frontoparietal (FPN) and salience network (SN) features during nonsymbolic magnitude processing alongside machine learning algorithms, we developed a framework to construct brain age prediction models for participants aged 7-30. Our study revealed differential developmental profiles in the synchronization within and between FPN and SN networks. Specifically, we observed a linear increase in FPN connectivity, concomitant with a decline in SN connectivity across the age span. A nonlinear U-shaped trajectory in the connectivity between the FPN and SN was discerned, revealing reduced FPN-SN synchronization among adolescents compared to both pediatric and adult cohorts. Leveraging the Gradient Boosting machine learning algorithm and nested fivefold stratified cross-validation with independent training datasets, we demonstrated that functional connectivity measures of the FPN and SN nodes predict chronological age, with a correlation coefficient of .727 and a mean absolute error of 2.944 between actual and predicted ages. Notably, connectivity within the FPN emerged as the most contributing feature for age prediction. Critically, a more matured brain age estimate is associated with better arithmetic performance. Our findings shed light on the intricate developmental changes occurring in the neural networks supporting magnitude representations. We emphasize brain age estimation as a potent tool for understanding cognitive development and its relationship to mathematical abilities across the critical developmental period of youth. PRACTITIONER POINTS: This study investigated the prolonged changes in the brain's architecture across childhood, adolescence, and adulthood, with a focus on task-state frontoparietal and salience networks. Distinct developmental pathways were identified: frontoparietal synchronization strengthens consistently throughout development, while salience network connectivity diminishes with age. Furthermore, adolescents show a unique dip in connectivity between these networks. Leveraging advanced machine learning methods, we accurately predicted individuals' ages based on these brain circuits, with a more mature estimated brain age correlating with better math skills.

Longitudinal neurofunctional changes in medication overuse headache patients after mindfulness practice in a randomized controlled trial (the MIND-CM study)

BackgroundMindfulness practice has gained interest in the management of Chronic Migraine associated with Medication Overuse Headache (CM-MOH). Mindfulness is characterized by present-moment self-awareness and relies on attention control and emotion regulation, improving headache-related pain management. Mindfulness modulates the Default Mode Network (DMN), Salience Network (SN), and Fronto-Parietal Network (FPN) functional connectivity. However, the neural mechanisms underlying headache-related pain management with mindfulness are still unclear. In this study, we tested neurofunctional changes after mindfulness practice added to pharmacological treatment as usual in CM-MOH patients.MethodsThe present study is a longitudinal phase-III single-blind Randomized Controlled Trial (MIND-CM study; NCT03671681). Patients had a diagnosis of CM-MOH, no history of neurological and severe psychiatric comorbidities, and were attending our specialty headache centre. Patients were divided in Treatment as Usual (TaU) and mindfulness added to TaU (TaU + MIND) groups. Patients underwent a neuroimaging and clinical assessment before the treatment and after one year. Longitudinal comparisons of DMN, SN, and FPN connectivity were performed between groups and correlated with clinical changes. Vertex-wise analysis was performed to assess cortical thickness changes.Results177 CM-MOH patients were randomized to either TaU group or TaU + MIND group. Thirty-four patients, divided in 17 TaU and 17 TaU + MIND, completed the neuroimaging follow-up. At the follow-up, both groups showed an improvement in most clinical variables, whereas only TaU + MIND patients showed a significant headache frequency reduction (p = 0.028). After one year, TaU + MIND patients showed greater SN functional connectivity with the left posterior insula (p-FWE = 0.007) and sensorimotor cortex (p-FWE = 0.026). In TaU + MIND patients only, greater SN-insular connectivity was associated with improved depression scores (r = -0.51, p = 0.038). A longitudinal increase in cortical thickness was observed in the insular cluster in these patients (p = 0.015). Increased anterior cingulate cortex thickness was also reported in TaU + MIND group (p-FWE = 0.02).ConclusionsIncreased SN-insular connectivity might modulate chronic pain perception and the management of negative emotions. Enhanced SN-sensorimotor connectivity could reflect improved body-awareness of painful sensations. Expanded cingulate cortex thickness might sustain improved cognitive processing of nociceptive information. Our findings unveil the therapeutic potential of mindfulness and the underlying neural mechanisms in CM-MOH patients.Trial RegistrationName of Registry; MIND-CM study; Registration Number ClinicalTrials.gov identifier: NCT0367168; Registration Date: 14/09/2018

Resting-state networks and anosognosia in Alzheimer's disease.

Recent evidence suggests that anosognosia or unawareness of cognitive impairment in Alzheimer's Disease (AD) may be explained by a disconnection between brain regions involved in accessing and monitoring information regarding self and others. It has been demonstrated that AD patients with anosognosia have reduced connectivity within the default mode network (DMN) and that anosognosia in people with prodromal AD is positively associated with bilateral anterior cingulate cortex (ACC), suggesting a possible role of this region in mechanisms of awareness in the early phase of disease. We hypothesized that anosognosia in AD is associated with an imbalance between the activity of large-scale resting-state functional magnetic resonance imaging (fMRI) networks, in particular the DMN, the salience network (SN), and the frontoparietal network (FPN). Sixty patients with MCI and AD dementia underwent fMRI and neuropsychological assessment including the Anosognosia Questionnaire Dementia (AQ-D), a measure of anosognosia based on a discrepancy score between patient's and carer's judgments. After having applied Independent Component Analysis (ICA) to resting fMRI data we performed: (i) correlations between the AQ-D score and functional connectivity in the DMN, SN, and FPN, and (ii) comparisons between aware and unaware patients of the DMN, SN, and FPN functional connectivity. We found that anosognosia was associated with (i) weak functional connectivity within the DMN, in posterior and middle cingulate cortex particularly, (ii) strong functional connectivity within the SN in ACC, and between the SN and basal ganglia, and (iii) a heterogenous effect concerning the functional connectivity of the FPN, with a weak connectivity between the FPN and PCC, and a strong connectivity between the FPN and ACC. The observed effects were controlled for differences in severity of cognitive impairment and age. Anosognosia in the AD continuum is associated with a dysregulation of the functional connectivity of three large-scale networks, namely the DMN, SN, and FPN.

Plasma Neurofilament Light Relates to Divergent Default and Salience Network Connectivity in Alzheimer's Disease and Behavioral Variant Frontotemporal Dementia.

Alzheimer's disease (AD) and behavioral variant frontotemporal dementia (bvFTD) show differential vulnerability to large-scale brain functional networks. Plasma neurofilament light (NfL), a promising biomarker of neurodegeneration, has been linked in AD patients to glucose metabolism changes in AD-related regions. However, it is unknown whether plasma NfL would be similarly associated with disease-specific functional connectivity changes in AD and bvFTD. Our study examined the associations between plasma NfL and functional connectivity of the default mode and salience networks in patients with AD and bvFTD. Plasma NfL and neuroimaging data from patients with bvFTD (n = 16) and AD or mild cognitive impairment (n = 38; AD + MCI) were analyzed. Seed-based functional connectivity maps of key regions within the default mode and salience networks were obtained and associated with plasma NfL in these patients. We demonstrated divergent associations between NfL and functional connectivity in AD + MCI and bvFTD patients. Specifically, AD + MCI patients showed lower default mode network functional connectivity with higher plasma NfL, while bvFTD patients showed lower salience network functional connectivity with higher plasma NfL. Further, lower NfL-related default mode network connectivity in AD + MCI patients was associated with lower Montreal Cognitive Assessment scores and higher Clinical Dementia Rating sum-of-boxes scores, although NfL-related salience network connectivity in bvFTD patients was not associated with Neuropsychiatric Inventory Questionnaire scores. Our findings indicate that plasma NfL is differentially associated with brain functional connectivity changes in AD and bvFTD.

Salience network connectivity is altered in 6-week-old infants at heightened likelihood for developing autism

Converging evidence implicates disrupted brain connectivity in autism spectrum disorder (ASD); however, the mechanisms linking altered connectivity early in development to the emergence of ASD symptomatology remain poorly understood. Here we examined whether atypicalities in the Salience Network – an early-emerging neural network involved in orienting attention to the most salient aspects of one’s internal and external environment – may predict the development of ASD symptoms such as reduced social attention and atypical sensory processing. Six-week-old infants at high likelihood of developing ASD based on family history exhibited stronger Salience Network connectivity with sensorimotor regions; infants at typical likelihood of developing ASD demonstrated stronger Salience Network connectivity with prefrontal regions involved in social attention. Infants with higher connectivity with sensorimotor regions had lower connectivity with prefrontal regions, suggesting a direct tradeoff between attention to basic sensory versus socially-relevant information. Early alterations in Salience Network connectivity predicted subsequent ASD symptomatology, providing a plausible mechanistic account for the unfolding of atypical developmental trajectories associated with vulnerability to ASD.

Resting-state networks and their relationship with MoCA performance in PD patients.

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.

Aberrant effective connectivity in Default Mode Network and Salience Network may reflect the hyperarousal state in chronic insomnia disorder

Aberrant effective connectivity in Default Mode Network and Salience Network may reflect the hyperarousal state in chronic insomnia disorder

Data-driven connectivity profiles relate to smoking cessation outcomes.

At a group level, nicotine dependence is linked to differences in resting-state functional connectivity (rs-FC) within and between three large-scale brain networks: the salience network (SN), default mode network (DMN), and frontoparietal network (FPN). Yet, individuals may display distinct patterns of rs-FC that impact treatment outcomes. This study used a data-driven approach, Group Iterative Multiple Model Estimation (GIMME), to characterize shared and person-specific rs-FC features linked with clinically-relevant treatment outcomes. 49 nicotine-dependent adults completed a resting-state fMRI scan prior to a two-week smoking cessation attempt. We used GIMME to identify group, subgroup, and individual-level networks of SN, DMN, and FPN connectivity. Regression models assessed whether within- and between-network connectivity of individual rs-FC models was associated with baseline cue-induced craving, and craving and use of regular cigarettes (i.e., "slips") during cessation. As a group, participants displayed shared patterns of connectivity within all three networks, and connectivity between the SN-FPN and DMN-SN. However, there was substantial heterogeneity across individuals. Individuals with greater within-network SN connectivity experienced more slips during treatment, while individuals with greater DMN-FPN connectivity experienced fewer slips. Individuals with more anticorrelated DMN-SN connectivity reported lower craving during treatment, while SN-FPN connectivity was linked to higher craving. In conclusion, in nicotine-dependent adults, GIMME identified substantial heterogeneity within and between the large-scale brain networks. Individuals with greater SN connectivity may be at increased risk for relapse during treatment, while a greater positive DMN-FPN and negative DMN-SN connectivity may be protective for individuals during smoking cessation treatment.

Functional connectivity trajectories in genetic frontotemporal dementia

AbstractBackgroundCharacterizing disease trajectories in frontotemporal lobar degeneration (FTLD) is essential to determine the optimal timing for initiating therapeutic interventions, and there is an urgent need for novel and sensitive disease biomarkers. Intrinsic connectivity network (ICN) mapping using task‐free fMRI is a promising biomarker which reveals early abnormalities even before symptomatic onset (Dopper et al. 2014; Lee et al. 2016). Yet, ICN trajectories from the presymptomatic to symptomatic stages in FTLD mutation carriers remain unclear.MethodIn this cross‐sectional study, we used UCSF and ALLFTD Consortia data to study 129 carriers with variants in MAPT (presymptomatic/prodromal/symptomatic: 34/4/7), C9orf72 (30/9/12) and GRN (22/4/7). Using cross‐sectional data to construct ICN trajectories by genotype, we built separate generalized additive models for each genetic group to estimate non‐linear relationships between standardized connectivity changes and disease age across clinical stages. ICN connectivity was based on seed‐based analyses for networks associated with common clinical syndromes for each genetic group (i.e., salience and default mode [MAPT/C9orf72/GRN], corticobasal syndrome [MAPT/GRN], progressive supranuclear palsy syndrome [MAPT], sensorimotor and medial pulvinar‐related [C9orf72], and non‐fluent variant primary progressive aphasia (nfvPPA) syndrome networks [GRN]). We included 127 healthy controls as a reference to calculate ICN z‐scores for each carrier. Each carrier’s disease age was defined as the difference between the carrier’s chronological age and estimated age of onset based on multimodal measures of structural imaging, fluid biomarker and clinical assessments (Staffaroni et al. 2022).ResultIn MAPT+, presymptomatic carriers showed declining salience network connectivity starting approximately 30 years before estimated onset, which plateaued about 20 years before onset. In C9orf72+, salience network hyperconnectivity emerged about 30 years before onset and declined throughout the presymptomatic and symptomatic stages. For GRN+, connectivity changes as a function of disease age were found within the salience and nfvPPA networks, with connectivity stable until around 10 years before estimated onset, followed by decline starting in the late presymptomatic phase and continuing through the prodromal and symptomatic stages.ConclusionThese findings demonstrate that FTLD genes show distinct ICN trajectories throughout the clinical spectrum. These results help pave the way for determining the optimal timing to initiate therapeutic interventions.

Functional connectivity trajectories in genetic frontotemporal dementia

AbstractBackgroundCharacterizing disease trajectories in frontotemporal lobar degeneration (FTLD) is essential to determine the optimal timing for initiating therapeutic interventions, and there is an urgent need for novel and sensitive disease biomarkers. Intrinsic connectivity network (ICN) mapping using task‐free fMRI is a promising biomarker which reveals early abnormalities even before symptomatic onset (Dopper et al. 2014; Lee et al. 2016). Yet, ICN trajectories from the presymptomatic to symptomatic stages in FTLD mutation carriers remain unclear.MethodIn this cross‐sectional study, we used UCSF and ALLFTD Consortia data to study 129 carriers with variants in MAPT (presymptomatic/prodromal/symptomatic: 34/4/7), C9orf72 (30/9/12) and GRN (22/4/7). Using cross‐sectional data to construct ICN trajectories by genotype, we built separate generalized additive models for each genetic group to estimate non‐linear relationships between standardized connectivity changes and disease age across clinical stages. ICN connectivity was based on seed‐based analyses for networks associated with common clinical syndromes for each genetic group (i.e., salience and default mode [MAPT/C9orf72/GRN], corticobasal syndrome [MAPT/GRN], progressive supranuclear palsy syndrome [MAPT], sensorimotor and medial pulvinar‐related [C9orf72], and non‐fluent variant primary progressive aphasia (nfvPPA) syndrome networks [GRN]). We included 127 healthy controls as a reference to calculate ICN z‐scores for each carrier. Each carrier’s disease age was defined as the difference between the carrier’s chronological age and estimated age of onset based on multimodal measures of structural imaging, fluid biomarker and clinical assessments (Staffaroni et al. 2022).ResultIn MAPT+, presymptomatic carriers showed declining salience network connectivity starting approximately 30 years before estimated onset, which plateaued about 20 years before onset. In C9orf72+, salience network hyperconnectivity emerged about 30 years before onset and declined throughout the presymptomatic and symptomatic stages. For GRN+, connectivity changes as a function of disease age were found within the salience and nfvPPA networks, with connectivity stable until around 10 years before estimated onset, followed by decline starting in the late presymptomatic phase and continuing through the prodromal and symptomatic stages.ConclusionThese findings demonstrate that FTLD genes show distinct ICN trajectories throughout the clinical spectrum. These results help pave the way for determining the optimal timing to initiate therapeutic interventions.