Intrinsic Connectivity Networks Research Articles

Change in resting state functional connectivity following working memory training in individuals with repetitive negative thinking

BackgroundRepetitive negative thinking (RNT) symptoms, which are characterized by pervasive, uncontrollable negative thoughts, are common in individuals with mood, anxiety, and traumatic stress disorders. Inability to regulate the contents of working memory is a hypothesized etiological factor in RNT, suggesting that training to improve working memory may be beneficial. This study examined the effects of working memory training on resting state functional connectivity (rsFC) in individuals with elevated RNT and whether such changes would be associated with clinical improvement. MethodsWe conducted a secondary analysis of pre-post resting state data collected as part of a randomized controlled trial [NCT04912089] of working memory training interventions (n=42) compared to a waitlist control group (n=23). We hypothesized that individuals completing training would show increased rsFC between the two key intrinsic connectivity networks - default mode network (posterior cingulate cortex; PCC) and frontoparietal network (dorsolateral prefrontal cortex; dlPFC). We explored whether magnitude of rsFC change was associated with change in RNT symptom severity. ResultsrsFC increased between the PCC and regions including frontal and parietal cortex in the training group relative to waitlist. Increased connectivity between the PCC and superior frontal cortex was associated with RNT symptom reduction. ConclusionsThese data provide evidence that working memory training can modulate neural circuitry at rest in individuals with RNT. Results align with accounts of working memory training effects on large-scale neurocircuitry changes and suggest that these changes may contribute to clinical promise of this type of intervention on transdiagnostic RNT symptoms.

Intrinsic functional connectivity of motor and heteromodal association cortex predicts individual differences in regulatory focus.

Regulatory focus theory (RFT) describes two cognitive-motivational systems for goal pursuit-the promotion and prevention systems-important for self-regulation and previously implicated in vulnerability to psychopathology. According to RFT, the promotion system is engaged in attaining ideal goals (e.g. hopes and dreams), whereas the prevention system is associated with accomplishing ought goals (e.g. duties and obligations). Prior task-based functional magnetic resonance imaging (fMRI) studies have mostly explored the mapping of these two systems onto the activity of a priori brain regions supporting motivation and executive control in both healthy and depressed adults. However, complex behavioral processes such as those guided by individual differences in regulatory focus are likely supported by widely distributed patterns of intrinsic functional connectivity. We used data-driven connectome-based predictive modeling to identify patterns of distributed whole-brain intrinsic network connectivity associated with individual differences in promotion and prevention system orientation in 1,307 young university volunteers. Our analyses produced a network model predictive of prevention but not promotion orientation, specifically the subjective experience of successful goal pursuit using prevention strategies. The predictive model of prevention success was highlighted by decreased intrinsic functional connectivity of both heteromodal association cortices in the parietal and limbic networks and the primary motor cortex. We discuss these findings in the context of strategic inaction, which drives individuals with a strong dispositional prevention orientation to inhibit their behavioral tendencies in order to shield the self from potential losses, thus maintaining the safety of the status quo but also leading to trade-offs in goal pursuit success.

Resting-state functional connectivity in children cooled for neonatal encephalopathy.

Therapeutic hypothermia improves outcomes following neonatal hypoxic-ischaemic encephalopathy, reducing cases of death and severe disability such as cerebral palsy compared with normothermia management. However, when cooled children reach early school-age, they have cognitive and motor impairments which are associated with underlying alterations to brain structure and white matter connectivity. It is unknown whether these differences in structural connectivity are associated with differences in functional connectivity between cooled children and healthy controls. Resting-state functional MRI has been used to characterize static and dynamic functional connectivity in children, both with typical development and those with neurodevelopmental disorders. Previous studies of resting-state brain networks in children with hypoxic-ischaemic encephalopathy have focussed on the neonatal period. In this study, we used resting-state fMRI to investigate static and dynamic functional connectivity in children aged 6-8 years who were cooled for neonatal hypoxic-ischaemic without cerebral palsy [n = 22, median age (interquartile range) 7.08 (6.85-7.52) years] and healthy controls matched for age, sex and socioeconomic status [n = 20, median age (interquartile range) 6.75 (6.48-7.25) years]. Using group independent component analysis, we identified 31 intrinsic functional connectivity networks consistent with those previously reported in children and adults. We found no case-control differences in the spatial maps of these intrinsic connectivity networks. We constructed subject-specific static functional connectivity networks by measuring pairwise Pearson correlations between component time courses and found no case-control differences in functional connectivity after false discovery rate correction. To study the time-varying organization of resting-state networks, we used sliding window correlations and deep clustering to investigate dynamic functional connectivity characteristics. We found k = 4 repetitively occurring functional connectivity states, which exhibited no case-control differences in dwell time, fractional occupancy or state functional connectivity matrices. In this small cohort, the spatiotemporal characteristics of resting-state brain networks in cooled children without severe disability were too subtle to be differentiated from healthy controls at early school-age, despite underlying differences in brain structure and white matter connectivity, possibly reflecting a level of recovery of healthy resting-state brain function. To our knowledge, this is the first study to investigate resting-state functional connectivity in children with hypoxic-ischaemic encephalopathy beyond the neonatal period and the first to investigate dynamic functional connectivity in any children with hypoxic-ischaemic encephalopathy.

Changes in Intrinsic Connectivity Networks Topology Across Levels of Dexmedetomidine-Induced Alteration of Consciousness.

Human consciousness is generally thought to emerge from the activity of intrinsic connectivity networks (resting-state networks [RSNs]) of the brain, which have topological characteristics including, among others, graph strength and efficiency. So far, most functional brain imaging studies in anesthetized subjects have compared wakefulness and unresponsiveness, a state considered as corresponding to unconsciousness. Sedation and general anesthesia not only produce unconsciousness but also phenomenological states of preserved mental content and perception of the environment (connected consciousness), and preserved mental content but no perception of the environment (disconnected consciousness). Unresponsiveness may be seen during unconsciousness, but also during disconnectedness. Deep dexmedetomidine sedation is frequently a state of disconnected consciousness. In this study, we were interested in characterizing the RSN topology changes across 4 different and steady-state levels of dexmedetomidine-induced alteration of consciousness, namely baseline (Awake, drug-free state), Mild sedation (drowsy, still responding), Deep sedation (unresponsive), and Recovery, with a focus on changes occurring between a connected consciousness state and an unresponsiveness state. A functional magnetic resonance imaging database acquired in 14 healthy volunteers receiving dexmedetomidine sedation was analyzed using a method combining independent component analysis and graph theory, specifically looking at changes in connectivity strength and efficiency occurring during the 4 above-mentioned dexmedetomidine-induced altered consciousness states. Dexmedetomidine sedation preserves RSN architecture. Unresponsiveness during dexmedetomidine sedation is mainly characterized by a between-networks graph strength alteration and within-network efficiency alteration of lower-order sensory RSNs, while graph strength and efficiency in higher-order RSNs are relatively preserved. The differential dexmedetomidine-induced RSN topological changes evidenced in this study may be the signature of inadequate processing of sensory information by lower-order RSNs, and of altered communication between lower-order and higher-order networks, while the latter remain functional. If replicated in an experimental paradigm distinguishing, in unresponsive subjects, disconnected consciousness from unconsciousness, such changes would sustain the hypothesis that disconnected consciousness arises from altered information handling by lower-order sensory networks and altered communication between lower-order and higher-order networks, while the preservation of higher-order networks functioning allows for an internally generated mental content (or dream).

Resting state functional connectivity differences following working memory training with massed exposure in individuals with public speaking anxiety

Exposure-based cognitive behavioral therapy (CBT) is a gold standard treatment for Social Anxiety Disorder (SAD), but many patients do not gain complete symptom relief. Since fear extinction is central to the effectiveness of exposure within CBT, adjunctive treatments that target neurocognitive systems underlying fear extinction could increase the effectiveness of CBT. Successful fear extinction and cognitive tasks like working memory share neurocognitive substrates. The present study evaluates the neural impact of working memory training (WMT) as an adjunctive CBT treatment by exploring changes in intrinsic network connectivity associated with combining WMT with exposure exercises. The sample included twenty-four adults (Mean Age = 27.42(9.75), 62.5% female) with elevated social anxiety symptoms. Participants completed either a WMT or sham training (ST) condition, followed by a speech-based massed exposure session (WMT+Exp versus ST+Exp). Compared to ST+Exp, WMT+Exp participants exhibited lower connectivity between the default and visual networks and visual and dorsal networks. Lower connectivity between these networks was associated with lower subjective distress at the end of the massed exposure across the whole sample. WMT+Exp completers exhibited unique functional connectivity between the frontoparietal and dorsal attention networks. WM+Exp was associated with a neural connectivity profile involving networks critical to working memory, fear learning, and emotion regulation, as well as emotional and sensory processing functions. Data provisionally point to combined working memory training and exposure facilitating improvement in neural connections useful for benefitting from CBT for SAD.

Higher-Order Intrinsic Brain Network Trajectories After Antipsychotic Treatment in Medication-Naïve Patients With First-Episode Psychosis

BackgroundIntrinsic brain network connectivity is already altered in first-episode psychosis (FEP), but the longitudinal trajectories of network connectivity, especially in response to antipsychotic treatment, remain poorly understood. The goal of this study was to investigate how antipsychotic medications affect higher-order intrinsic brain network connectivity in FEP. MethodsData from 87 antipsychotic medication-naïve patients with FEP and 87 healthy control participants were used. Medication-naïve patients received antipsychotic treatment for 16 weeks. Resting-state functional connectivity (FC) of the default mode, salience, dorsal attention, and executive control networks were assessed prior to treatment and at 6 and 16 weeks after treatment. We evaluated baseline and FC changes using linear mixed models to test group × time interactions within each network. Associations between FC changes after 16 weeks and response to treatment were also evaluated. ResultsPrior to treatment, significant group differences in all networks were found. However, significant trajectory changes in FC were found only in the default mode and executive control networks. Changes in FC in these networks were associated with treatment response. Several sensitivity analyses showed a consistent normalization of executive control network FC in response to antipsychotic treatment. ConclusionsHere, we found that alterations in intrinsic brain network FC were not only alleviated with antipsychotic treatment, but the extent of this normalization was also associated with the degree of reduction in symptom severity. Taken together, our data suggest modulation of intrinsic brain network connectivity (mainly frontoparietal connectivity) as a mechanism underlying antipsychotic treatment response in FEP.

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.

Interventional clinical trial findings from targeted multiday repetitive transcranial magnetic stimulation to treat memory loss in amnestic mild cognitive impairment

AbstractBackgroundMemory loss is the hallmark cognitive symptom of Alzheimer’s disease (AD), and it affects independence, autonomy, and identity. AD‐related memory deficits are associated with pathological changes in brain structure and function, and current treatments offer limited relief. Targeted repetitive transcranial magnetic stimulation (rTMS) of AD‐vulnerable intrinsic brain networks can enhance memory abilities in healthy adults (Wang et al., 2014). To test rTMS approaches as a potential treatment for clinical memory loss, we administered a local clinical trial (ClinicalTrials.gov #alz078533) that enrolled patients with amnestic mild cognitive impairment (aMCI), a frequent precursor to AD (target enrollment of 16). Here, we report cognitive and brain findings from our trial.MethodsPatients with aMCI completed two weeklong interventions consisting of pre‐stimulation brain and cognitive measurement, rTMS for five consecutive days, and post‐stimulation brain and cognitive measurement. Brain measures included structural and resting‐state functional MRI data; cognitive assessments included measures of memory function. Interventions were identically formatted except for rTMS intensity (treatment/sham). Stimulation used β‐frequency pulse sequences which alternated 2‐sec. 20 Hz stimulation with 28‐sec. rest for 20 min (1600 pulses); stimulation location was a left lateral parietal cortex location coactive with a hippocampus‐centered functional network. Stimulation intensity varied with each participant’s resting motor threshold (treatment, 100%; sham, 10%). Condition order was counterbalanced.ResultsWe identified hippocampus‐centered networks in each participant, then localized parietal rTMS targets. Critically, we observed changes in brain and cognitive (memory) measures in the treatment‐intensity condition that were not observed in the sham‐intensity condition. Furthermore, we observed changes in intrinsic network connectivity within the stimulated hippocampus‐centered network.ConclusionsOur trial of patients with aMCI measured changes in brain and cognitive variables after rTMS of a brain network supporting memory processes. We found evidence consistent with neural plasticity, and we frequently observed memory improvement in patients with aMCI after treatment‐intensity rTMS. Our findings suggest that rTMS can improve memory in clinical populations. This is important because, counterintuitively, new disease modifying therapies for AD may increase need for symptomatic treatment of memory loss due to prolongation of prodromal/mild stages of AD. Thus, adjuvant therapies such as rTMS for memory loss could improve AD treatment outcomes.

Interventional clinical trial findings from targeted multiday repetitive transcranial magnetic stimulation to treat memory loss in amnestic mild cognitive impairment

AbstractBackgroundMemory loss is the hallmark cognitive symptom of Alzheimer’s disease (AD), and it affects independence, autonomy, and identity. AD‐related memory deficits are associated with pathological changes in brain structure and function, and current treatments offer limited relief. Targeted repetitive transcranial magnetic stimulation (rTMS) of AD‐vulnerable intrinsic brain networks can enhance memory abilities in healthy adults (Wang et al., 2014). To test rTMS approaches as a potential treatment for clinical memory loss, we administered a local clinical trial (ClinicalTrials.gov #alz081816) that enrolled patients with amnestic mild cognitive impairment (aMCI), a frequent precursor to AD (target enrollment of 16). Here, we report cognitive and brain findings from our trial.MethodPatients with aMCI completed two weeklong interventions consisting of pre‐stimulation brain and cognitive measurement, rTMS for five consecutive days, and post‐stimulation brain and cognitive measurement. Brain measures included structural and resting‐state functional MRI data; cognitive assessments included measures of memory function. Interventions were identically formatted except for rTMS intensity (treatment/sham). Stimulation used ß‐frequency pulse sequences which alternated 2‐sec. 20 Hz stimulation with 28‐sec. rest for 20 min (1600 pulses); stimulation location was a left lateral parietal cortex location coactive with a hippocampus‐centered functional network. Stimulation intensity varied with each participant’s resting motor threshold (treatment, 100%; sham, 10%). Condition order was counterbalanced.ResultWe identified hippocampus‐centered networks in each participant, then localized parietal rTMS targets. Critically, we observed changes in brain and cognitive (memory) measures in the treatment‐intensity condition that were not observed in the sham‐intensity condition. Furthermore, we observed changes in intrinsic network connectivity within the stimulated hippocampus‐centered network.ConclusionOur trial of patients with aMCI measured changes in brain and cognitive variables after rTMS of a brain network supporting memory processes. We found evidence consistent with neural plasticity, and we frequently observed memory improvement in patients with aMCI after treatment‐intensity rTMS. Our findings suggest that rTMS can improve memory in clinical populations. This is important because, counterintuitively, new disease modifying therapies for AD may increase need for symptomatic treatment of memory loss due to prolongation of prodromal/mild stages of AD. Thus, adjuvant therapies such as rTMS for memory loss could improve AD treatment outcomes.

Within‐network Functional Connectivity of Intrinsic Networks in SuperAgers

AbstractBackgroundMemory decline in late life is a hallmark of aging, yet SuperAgers are individuals age 80 or older with episodic memory performance at least as good as cognitively average 50‐to‐60‐year‐olds. Neuroimaging analyses have found SuperAgers to have thicker cortices and slower atrophy rates compared to similarly aged controls (Controls). This project extended the anatomical findings by examining the functional integrity of seven intrinsic networks spanning the entire cortex and two memory‐specific systems identified from task‐based and resting state studies.MethodsWithin‐network functional connectivity (FC) of seven large‐scale networks and two memory systems were compared between 25 SuperAgers and 16 Controls using resting state functional MRI (rs‐fMRI) and T1‐weighted structural imaging from a single visit. Classification of SuperAgers/Controls was determined based on measures of episodic memory, executive functioning, verbal fluency, and picture naming (Harrison et al., 2012). Inclusion criteria required stable cognitive status across two visits. In the first analysis, we included all seven networks from a common resting‐state atlas (Schaefer et al., 2018). Within‐network FCs for all networks were defined as the average FCs between all within‐network regions (Figure 1A). In the second analysis, we investigated two memory‐specific networks: the anterior temporal (AT) and posterior medial (PM) systems. AT and PM cortical maps (Figure 1B) were identified from prior research (de Flores et al., 2022). Within‐network FC of the AT and PM systems were defined as the FC between AT‐to‐anterior‐hippocampus and PM‐to‐posterior‐hippocampus, respectively. For both analyses, FCs were compared across groups using two‐sample independent t‐tests and corrected for multiple comparisons (Benjamini‐Hochberg false discovery rate).ResultsWe found no significant between‐group differences in demographic characteristics including age, sex, and education. Performance on neuropsychological measures was significantly different for episodic memory, verbal fluency, and picture naming. Group differences in within‐network FCs for large‐scale networks and memory systems were nonsignificant.ConclusionAt the group‐level, within‐network FC of large‐scale networks and memory‐specific systems were not a primary differentiator between cognitively average aging and SuperAging phenotypes. Person‐specific functional connectome approaches may be important for understanding network organizational features of SuperAgers.

Neural basis underlying the relation between internet addiction tendency and sleep quality: The intrinsic default-mode network connectivity pathways

Internet addiction (IA) tendency is considered an addictive behavior that results from excessive Internet use, and severely affecting an individual's physical health, emotion, and sleep. Although previous studies indicated that IA tendency was negatively correlated with sleep quality, the underlying neural basis of this relationship remained unclear. To address this issue, we utilized resting-state functional connectivity (RSFC) analysis to identify the neural pathways of the relationship between IA tendency and sleep quality. The behavioral results indicated a positive correlation between these two factors. And RSFC results revealed that IA tendency was positively related to the strength of functional connectivity within the default-mode network (DMN), including the right precuneus-left middle temporal gyrus (rPrcu-lMTG), the left anterior cingulate-left superior frontal gyrus (lAC-lSFG), and the left inferior parietal lobe-left medial superior frontal gyrus (lIPL-lMSFG). More importantly, mediation analysis demonstrated that IA tendency could mediate the relationship between these functional couplings and sleep quality. In conclusion, our findings suggest that intrinsic DMN connectivity may be an important neural pathways underlying the effects of IA tendency on sleep quality, and provide neural evidence for understanding the relationship between IA tendency and sleep quality.

Whole brain network effects of subcallosal cingulate deep brain stimulation for treatment-resistant depression

Ongoing experimental studies of subcallosal cingulate deep brain stimulation (SCC DBS) for treatment-resistant depression (TRD) show a differential timeline of behavioral effects with rapid changes after initial stimulation, and both early and delayed changes over the course of ongoing chronic stimulation. This study examined the longitudinal resting-state regional cerebral blood flow (rCBF) changes in intrinsic connectivity networks (ICNs) with SCC DBS for TRD over 6 months and repeated the same analysis by glucose metabolite changes in a new cohort. A total of twenty-two patients with TRD, 17 [15 O]-water and 5 [18 F]-fluorodeoxyglucose (FDG) positron emission tomography (PET) patients, received SCC DBS and were followed weekly for 7 months. PET scans were collected at 4-time points: baseline, 1-month after surgery, and 1 and 6 months of chronic stimulation. A linear mixed model was conducted to examine the differential trajectory of rCBF changes over time. Post-hoc tests were also examined to assess postoperative, early, and late ICN changes and response-specific effects. SCC DBS had significant time-specific effects in the salience network (SN) and the default mode network (DMN). The rCBF in SN and DMN was decreased after surgery, but responder and non-responders diverged thereafter, with a net increase in DMN activity in responders with chronic stimulation. Additionally, the rCBF in the DMN uniquely correlated with depression severity. The glucose metabolic changes in a second cohort show the same DMN changes. The trajectory of PET changes with SCC DBS is not linear, consistent with the chronology of therapeutic effects. These data provide novel evidence of both an acute reset and ongoing plastic effects in the DMN that may provide future biomarkers to track clinical improvement with ongoing treatment.

Opponent intrinsic brain network connectivity profiles associated with posttraumatic fear and dysphoria symptoms in trauma-exposed refugees.

Resting-state functional magnetic resonance imaging (rsfMRI) studies report functional alterations in the connectivity between intrinsic brain networks in posttraumatic stress disorder (PTSD), but PTSD heterogeneity is rarely considered. Evidence points to fear (e.g., reexperiencing) and dysphoria (e.g., withdrawal) symptom factors as important in PTSD presentations, including relating to variable emotion dysregulation patterns. This study, therefore, tested how fear and dysphoria posttraumatic symptoms were differentially associated with core network connectivity and emotion dysregulation behaviors in a large group of trauma-exposed refugees. A final sample of 77 trauma-exposed participants completed a rsfMRI scan. Independent component analysis identified active networks and functional network connectivity (FNC) between networks was assessed. Fear and dysphoria posttraumatic symptoms were partially correlated with FNCs, and linear regression models examined relationships with self-reported difficulties in emotion regulation. Twenty-three active networks were identified, eight being in the networks of interest (p < .05 false discovery rate-corrected). Fear and dysphoria symptoms were specifically related to connectivity patterns between two subnetworks of the default mode network (DMN). Fear symptoms were negatively associated with anterior dorsomedial DMN (admDMN) and temporoparietal DMN (tpDMN) connectivity; whereas dysphoria symptoms were positively associated with admDMN-tpDMN connectivity. Additionally, admDMN-tpDMN connectivity was positively predicted by goal-directed emotion dysregulation but negatively predicted by poor emotional clarity. Fear and dysphoria posttraumatic symptoms showed opponent associations with admDMN and tpDMN connectivity, potentially reflecting patterns of under- and overemotion dysregulation associated with these symptom profiles respectively. Findings highlight the importance of considering posttraumatic heterogeneity when constructing neural models of PTSD. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Supplemental Material for Opponent Intrinsic Brain Network Connectivity Profiles Associated with Posttraumatic Fear and Dysphoria Symptoms in Trauma-Exposed Refugees

Supplemental Material for Opponent Intrinsic Brain Network Connectivity Profiles Associated with Posttraumatic Fear and Dysphoria Symptoms in Trauma-Exposed Refugees

SAT412 Effects Of Gender-Affirming Hormone Therapy On The Connectivity Of Intrinsic Brain Networks

Abstract Disclosure: C.C. Pedreira: None. S. Tchir-Bourgeois: None. S. Tuli: None. A. Giancola: None. C. Loxton: None. A.S. Keuroghlian: None. M. Misra: None. J.M. Andreano: None. Background: Previous research has indicated that both acute gonadal hormone treatments and fluctuations in ovarian hormone levels over the course of the menstrual cycle can significantly alter patterns of communication between brain regions, particularly regions involved in affective processing. However, the neural effects of prolonged exogenous gonadal hormone exposure, as in gender-affirming hormone therapy (GAHT), are not presently well-understood. A better understanding of the influence of GAHT on intrinsic network connectivity could point the way towards improved GAHT treatment regimens that minimize affective side effects.Objective: To characterize the effects of estradiol and testosterone treatments in GAH on patterns of connectivity within and between the brain’s intrinsic networks.Methods: 5 transgender individuals receiving GAHT (estradiol n =3, testosterone n = 2) were scanned using functional magnetic imaging (fMRI) at rest at two timepoints: baseline, prior to treatment, and 6 months into GAHT. The time course of neural activity was computed for each voxel in the brain, then tested for correlation with each other voxel to develop a whole-brain connectome for each participant. Connectomes were then analyzed in two ways: 1) maps of average connectivity to two regions of interest found in previous research to differ between cis and transgender people (the anterior insula and temporal pole) were generated for each participant. These maps were then compared between baseline and 6-month timepoints. 2) Overall network structure of the brain was generated a priori for each participant at each timepoint using a community detection algorithm. Network assignments were then compared between timepoints, noting regions whose connectivity shifted between networks after GAHT.Results: 2 of 3 participants treated with estradiol exhibited a significant reduction of connectivity to the anterior insula throughout the brain, most notably within the medial temporal lobe and cingulate cortex. Both participants receiving testosterone treatment showed reduced anterior insula connectivity, although connectivity to the cingulate cortex, particularly the mid-cingulate, was preserved. Estradiol did not significantly affect connectivity of the frontal pole, although testosterone produced a widespread reduction in frontal pole connectivity. Community detection analysis indicated a shift in connectivity to the salience network from the default mode network in the medial temporal lobe following estradiol treatment. Testosterone treatment was associated with greater connectivity in medial frontal regions to the frontoparietal network. Conclusions: Preliminary evidence indicates that both estradiol and testosterone treatment can produce significant changes in the connectivity of affective regions in the brain, as well as reorganization of the brain’s network structure. Presentation: Saturday, June 17, 2023

Identifying canonical and replicable multi-scale intrinsic connectivity networks in 100k+ resting-state fMRI datasets.

Despite the known benefits of data-driven approaches, the lack of approaches for identifying functional neuroimaging patterns that capture both individual variations and inter-subject correspondence limits the clinical utility of rsfMRI and its application to single-subject analyses. Here, using rsfMRI data from over 100k individuals across private and public datasets, we identify replicable multi-spatial-scale canonical intrinsic connectivity network (ICN) templates via the use of multi-model-order independent component analysis (ICA). We also study the feasibility of estimating subject-specific ICNs via spatially constrained ICA. The results show that the subject-level ICN estimations vary as a function of the ICN itself, the data length, and the spatial resolution. In general, large-scale ICNs require less data to achieve specific levels of (within- and between-subject) spatial similarity with their templates. Importantly, increasing data length can reduce an ICN's subject-level specificity, suggesting longer scans may not always be desirable. We also find a positive linear relationship between data length and spatial smoothness (possibly due to averaging over intrinsic dynamics), suggesting studies examining optimized data length should consider spatial smoothness. Finally, consistency in spatial similarity between ICNs estimated using the full data and subsets across different data lengths suggests lower within-subject spatial similarity in shorter data is not wholly defined by lower reliability in ICN estimates, but may be an indication of meaningful brain dynamics which average out as data length increases.

Functional connectivity mediates the relationship between cardiorespiratory fitness and stress in midlife.

BackgroundIncreasing evidence suggests that the relation between mental health and physical health is bidirectional and underpinned by complex neural systems. Cardiovascular fitness is a key measure of physical health but its relation to mental health is insufficiently examined. Characterizing the neural mechanisms by which cardiovascular fitness influences mental health could inform the development of strategies to promote mental health and minimize the risk of mental disorders. Methods and resultsThe relation between cardiorespiratory fitness, functional brain connectivity and mental health was studied in 418 healthy middle-aged (aged 40–65 years) adult participants of the Barcelona Brain Health Initiative (BBHI). Higher cardiorespiratory fitness, measured by VO₂ peak, was associated with lower symptoms of anxiety (β = −0.111, p = 0.017) and stress (β = −0.242, p = 0.002) scores, evaluated by the Depression Anxiety and Stress Scale (DASS-21) and its three subscales (stress, anxiety, and depression). Higher within-network functional connectivity of the Default Mode Network (DMN) was associated with higher VO₂ peak (β = 0.195, p = 0.002), and lower stress scores (β = −0.126, p = 0.011). In addition, higher functional connectivity between the Frontoparietal Network (FPN) and Salience Network (SN) was associated with higher VO₂ peak (β = 0.187, p = 0.002), and lower stress scores (β = −0.123, p = 0.016). Both within-DMN [ACME = −0.02 (-0.04,-0.00), p = 0.040] and between FPN-SN [ACME = −0.01 (-0.04,-0.00), p = 0.036] functional connectivity mediated the relationship between cardiorespiratory fitness and stress. ConclusionsThe relationship between the cardiorespiratory fitness and stress in middle-aged adults is mediated by functional connectivity of several intrinsic resting-state networks. These results highlight a potential mechanistic pathway through which higher cardiorespiratory fitness can positively impact brain health in midlife.

Related neural networks underlie suppression of emotion, memory, motor processes as identified by data-driven analysis

BackgroundGoal-directed behavior benefits from self-regulation of cognitive and affective processes, such as emotional reactivity, memory retrieval, and prepotent motor response. Dysfunction in self-regulation is a common characteristic of many psychiatric disorders, such as PTSD and ADHD. This study sought to determine whether common intrinsic connectivity networks (ICNs; e.g. default mode network) are involved in the regulation of emotion, motor, and memory processes, and if a data-driven approach using independent component analysis (ICA) would successfully identify such ICNs that contribute to inhibitory regulation.MethodsEighteen participants underwent neuroimaging while completing an emotion regulation (ER) task, a memory suppression (Think/No-Think; TNT) task, and a motor inhibition (Stop Signal; SS) task. ICA (CONN; MATLAB) was conducted on the neuroimaging data from each task and corresponding components were selected across tasks based on interrelated patterns of activation. Subsequently, ICNs were correlated with behavioral performance variables from each task.ResultsICA indicated a common medial prefrontal network, striatal network, and frontoparietal executive control network, as well as downregulation in task-specific ROIs.ConclusionsThese results illustrate that common ICNs were exhibited across three distinct inhibitory regulation tasks, as successfully identified through a data-driven approach (ICA).

Multimodal fusion of multiple rest fMRI networks and MRI gray matter via parallel multilink joint ICA reveals highly significant function/structure coupling in Alzheimer's disease.

In this article, we focus on estimating the joint relationship between structural magnetic resonance imaging (sMRI) gray matter (GM), and multiple functional MRI (fMRI) intrinsic connectivity networks (ICNs). To achieve this, we propose a multilink joint independent component analysis (ml-jICA) method using the same core algorithm as jICA. To relax the jICA assumption, we propose another extension called parallel multilink jICA (pml-jICA) that allows for a more balanced weight distribution over ml-jICA/jICA. We assume a shared mixing matrix for both the sMRI and fMRI modalities, while allowing for different mixing matrices linking the sMRI data to the different ICNs. We introduce the model and then apply this approach to study the differences in resting fMRI and sMRI data from patients with Alzheimer's disease (AD) versus controls. The results of the pml-jICA yield significant differences with large effect sizes that include regions in overlapping portions of default mode network, and also hippocampus and thalamus. Importantly, we identify two joint components with partially overlapping regions which show opposite effects for AD versus controls, but were able to be separated due to being linked to distinct functional and structural patterns. This highlights the unique strength of our approach and multimodal fusion approaches generally in revealing potentially biomarkers of brain disorders that would likely be missed by a unimodal approach. These results represent the first work linking multiple fMRI ICNs to GM components within a multimodal data fusion model and challenges the typical view that brain structure is more sensitive to AD than fMRI.