Task-based Functional Connectivity Research Articles

23. Capturing Dynamic Patterns of Task-Based Functional Connectivity During Drug Cue Reactivity in Fronto-Amygdala Circuit

23. Capturing Dynamic Patterns of Task-Based Functional Connectivity During Drug Cue Reactivity in Fronto-Amygdala Circuit

Age-related changes of interoceptive brain networks: Implications for interoception and alexithymia.

Aging is known to be associated with a decline in interoceptive abilities and changes in emotional processing, including alexithymia. As the brain areas supporting interoceptive awareness participate in the perception of emotion, we suggested that interoceptive decline and alexithymia in older adults may share common neural ground. To test this hypothesis, we administered functional magnetic resonance imaging-based heartbeat detection task to 62 adults of diverse ages (range 18-73) and evaluated a larger sample of older and younger adults using questionnaires characterizing interoceptive sensibility, alexithymia, and depressive attitudes. We found that increasing age was linked to decreased activation during the interoceptive task, including the right insular-opercular and supplementary motor areas (SMAs). Age also affected task-based functional connectivity, with two major effects being a decrease in the connectivity of the SMA-insular network and an increase in the connectivity of the prefrontal-lateral occipital network. Path analysis performed for interoceptive accuracy as the endogenous variable revealed that the impact of age was mediated by the functional activation of the insular cortex and SMA and by the connectivity between these areas. Another path analysis using alexithymia as the endogenous variable while controlling for depressive attitudes showed that the effect of age was mediated by interoceptive decline. The study supports the role of central mechanisms in age-related interoceptive decline and shows its implications for alexithymia. Since alexithymia represents a risk factor for mental and cardiovascular diseases, the study findings may open an important direction toward maintaining older adults' well-being. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

The impact of a tDCS and cognitive training intervention on task-based functional connectivity.

Declines in several cognitive domains, most notably processing speed, occur in non-pathological aging. Given the exponential growth of the older adult population, declines in cognition serve as a significant public health issue that must be addressed. Promising studies have shown that cognitive training in older adults, particularly using the useful field of view (UFOV) paradigm, can improve cognition with moderate to large effect sizes. Additionally, meta-analyses have found that transcranial direct current stimulation (tDCS), a non-invasive form of brain stimulation, can improve cognition in attention/processing speed and working memory. However, only a handful of studies have looked at concomitant tDCS and cognitive training, usually with short interventions and small sample sizes. The current study assessed the effect of a tDCS (active versus sham) and a 3-month cognitive training intervention on task-based functional connectivity during completion of the UFOV task in a large older adult sample (N = 153). We found significant increased functional connectivity between the left and right pars triangularis (the ROIs closest to the electrodes) following active, but not sham tDCS. Additionally, we see trending behavioral improvements associated with these functional connectivity changes in the active tDCS group, but not sham. Collectively, these findings suggest that tDCS and cognitive training can be an effective modulator of task-based functional connectivity above and beyond a cognitive training intervention alone.

Improved estimation of general cognitive ability and its neural correlates with a large battery of cognitive tasks.

Elucidating the neural mechanisms of general cognitive ability (GCA) is an important mission of cognitive neuroscience. Recent large-sample cohort studies measured GCA through multiple cognitive tasks and explored its neural basis, but they did not investigate how task number, factor models, and neural data type affect the estimation of GCA and its neural correlates. To address these issues, we tested 1,605 Chinese young adults with 19 cognitive tasks and Raven's Advanced Progressive Matrices (RAPM) and collected resting state and n-back task fMRI data from a subsample of 683 individuals. Results showed that GCA could be reliably estimated by multiple tasks. Increasing task number enhances both reliability and validity of GCA estimates and reliably strengthens their correlations with brain data. The Spearman model and hierarchical bifactor model yield similar GCA estimates. The bifactor model has better model fit and stronger correlation with RAPM but explains less variance and shows weaker correlations with brain data than does the Spearman model. Notably, the n-back task-based functional connectivity patterns outperform resting-state fMRI in predicting GCA. These results suggest that GCA derived from a multitude of cognitive tasks serves as a valid measure of general intelligence and that its neural correlates could be better characterized by task fMRI than resting-state fMRI data.

Motor experience modulates neural processing of lexical action language: Evidence from rugby players

The perceptual symbol theory proposes a sensorimotor simulation in language processing, emphasizing the role of motor experience. However, the neural basis of motor experience on lexical-level language processing remains little known. In the current fMRI study, we compared brain activation and task-based functional connectivity in 28 rugby players and 28 novices during rugby- specialized and daily verb processing. Distinct differences were observed between the two groups in the bilateral superior temporal gyrus and left angular gyrus regions during specialized verb processing. Notably, intergroup functional connectivity was evident between the left superior temporal gyrus and the right precentral gyrus during specialized verb processing. This study contributes insights into the neural responses and connectivity patterns associated with motor experience at the lexical level, highlighting its potential impact on language processing.

Dose-response in modulating brain function with transcranial direct current stimulation: From local to network levels.

Understanding the dose-response relationship is crucial in studying the effects of brain stimulation techniques, such as transcranial direct current stimulation (tDCS). The dose-response relationship refers to the relationship between the received stimulation dose and the resulting response, which can be described as a function of the dose at various levels, including single/multiple neurons, clusters, regions, or networks. Here, we are focused on the received stimulation dose obtained from computational head models and brain responses which are quantified by functional magnetic resonance imaging (fMRI) data. In this randomized, triple-blind, sham-controlled clinical trial, we recruited sixty participants with methamphetamine use disorders (MUDs) as a sample clinical population who were randomly assigned to receive either sham or active tDCS. Structural and functional MRI data, including high-resolution T1 and T2-weighted MRI, resting-state functional MRI, and a methamphetamine cue-reactivity task fMRI, were acquired before and after tDCS. Individual head models were generated using the T1 and T2-weighted MRI data to simulate electric fields. In a linear approach, we investigated the associations between electric fields (received dose) and changes in brain function (response) at four different levels: voxel level, regional level (using atlas-based parcellation), cluster level (identifying active clusters), and network level (task-based functional connectivity). At the voxel level, regional level, and cluster level, no FDR-corrected significant correlation was observed between changes in functional activity and electric fields. However, at the network level, a significant positive correlation was found between frontoparietal connectivity and the electric field at the frontopolar stimulation site (r = 0.42, p corrected = 0.02; medium effect size). Our proposed pipeline offers a methodological framework for analyzing tDCS effects by exploring dose-response relationships at different levels, enabling a direct link between electric field variability and the neural response to tDCS. The results indicate that network-based analysis provides valuable insights into the dependency of tDCS neuromodulatory effects on the individual's regional current dose. Integration of dose-response relationships can inform dose optimization, customization, or the extraction of predictive/treatment-response biomarkers in future brain stimulation studies.

Graded functional organization in the left inferior frontal gyrus: evidence from task-free and task-based functional connectivity.

The left inferior frontal gyrus has been ascribed key roles in numerous cognitive domains, such as language and executive function. However, its functional organization is unclear. Possibilities include a singular domain-general function, or multiple functions that can be mapped onto distinct subregions. Furthermore, spatial transition in function may be either abrupt or graded. The present study explored the topographical organization of the left inferior frontal gyrus using a bimodal data-driven approach. We extracted functional connectivity gradients from (i) resting-state fMRI time-series and (ii) coactivation patterns derived meta-analytically from heterogenous sets of task data. We then sought to characterize the functional connectivity differences underpinning these gradients with seed-based resting-state functional connectivity, meta-analytic coactivation modeling and functional decoding analyses. Both analytic approaches converged on graded functional connectivity changes along 2 main organizational axes. An anterior-posterior gradient shifted from being preferentially associated with high-level control networks (anterior functional connectivity) to being more tightly coupled with perceptually driven networks (posterior). A second dorsal-ventral axis was characterized by higher connectivity with domain-general control networks on one hand (dorsal functional connectivity), and with the semantic network, on the other (ventral). These results provide novel insights into an overarching graded functional organization of the functional connectivity that explains its role in multiple cognitive domains.

Task and Resting-State Functional Connectivity Predict Driving Violations.

Aberrant driving behaviors cause accidents; however, there is a lack of understanding of the neural mechanisms underlying these behaviors. To address this issue, a task and resting-state functional connectivity was used to predict aberrant driving behavior and associated personality traits. The study included 29 right-handed participants with driving licenses issued for more than 1 year. During the functional magnetic resonance imaging experiment, participants first recorded their resting state and then watched a driving video while continuously rating the risk and speed on each block. Functional connectome-based predictive modeling was employed for whole brain tasks and resting-state functional connectivity to predict driving behavior (violation, error, and lapses), sensation-seeking, and impulsivity. Resting state and task-based functional connectivity were found to significantly predict driving violations, with resting state significantly predicting lapses and task-based functional connectivity showing a tendency to predict errors. Conversely, neither impulsivity nor sensation-seeking was associated with functional connectivity. The results suggest a significant association between aberrant driving behavior, but a nonsignificant association between impulsivity and sensation-seeking, and task-based or resting state functional connectivity. This could provide a deeper understanding of the neural processing underlying reckless driving that may ultimately be used to prevent accidents.

Simple topological task-based functional connectivity features predict longitudinal behavioral change of fluid reasoning in the RANN cohort

Recent attention has been given to topological data analysis (TDA), and more specifically persistent homology (PH), to identify the underlying shape of brain network connectivity beyond simple edge pairings by computing connective components across different connectivity thresholds (see Sizemore et al., 2019). In the present study, we applied PH to task-based functional connectivity, computing 0-dimension Betti (B0) curves and calculating the area under these curves (AUC); AUC indicates how quickly a single connected component is formed across correlation filtration thresholds, with lower values interpreted as potentially analogous to lower whole-brain system segregation (e.g., Gracia-Tabuenca et al., 2020). One hundred sixty-three participants from the Reference Ability Neural Network (RANN) longitudinal lifespan cohort (age 20–80 years) were tested in-scanner at baseline and five-year follow-up on a battery of tests comprising four domains of cognition (i.e., Stern et al., 2014). We tested for 1.) age-related change in the AUC of the B0 curve over time, 2.) the predictive utility of AUC in accounting for longitudinal change in behavioral performance and 3.) compared system segregation to the PH approach. Results demonstrated longitudinal age-related decreases in AUC for Fluid Reasoning, with these decreases predicting longitudinal declines in cognition, even after controlling for demographic and brain integrity factors; moreover, change in AUC partially mediated the effect of age on change in cognitive performance. System segregation also significantly decreased with age in three of the four cognitive domains but did not predict change in cognition. These results argue for greater application of TDA to the study of aging.

Task difficulty modulates age-related differences in functional connectivity during word production

Older adults typically report increased difficulty with language production, while its neural bases are less clear. The current study investigated the neural bases of age-related differences in language production at the word level and the modulating effect of task difficulty, focusing on task-based functional connectivity. Using an English phonological Go/No-Go picture naming task, task difficulty was manipulated by varying the proportion of naming trials (Go trials) and inhibition trials (No-Go trials) across runs. Behaviorally, compared to younger adults, older adults performed worse, and showed larger effects of task difficulty. Neurally, older adults had lower within language network connectivity compared to younger adults. Moreover, older adults’ language network became less segregated as task difficulty increased. These results are consistent with the Compensation-Related Utilization of Neural Circuits Hypothesis, suggesting that the brain becomes less specified and efficient with increased task difficulty, and that these effects are stronger among older adults (i.e., more dedifferentiated).

Functional network reconfiguration supporting memory-guided attention.

Studies have identified several brain regions whose activations facilitate attentional deployment via long-term memories. We analyzed task-based functional connectivity at the network and node-specific level to characterize large-scale communication between brain regions underlying long-term memory guided attention. We predicted default mode, cognitive control, and dorsal attention subnetworks would contribute differentially to long-term memory guided attention, such that network-level connectivity would shift based on attentional demands, requiring contribution of memory-specific nodes within default mode and cognitive control subnetworks. We expected that these nodes would increase connectivity with one another and with dorsal attention subnetworks during long-term memory guided attention. Additionally, we hypothesized connectivity between cognitive control and dorsal attention subnetworks facilitating external attentional demands. Our results identified both network-based and node-specific interactions that facilitate different components of LTM-guided attention, suggesting a crucial role across the posterior precuneus and restrosplenial cortex, acting independently from the divisions of default mode and cognitive control subnetworks. We found a gradient of precuneus connectivity, with dorsal precuneus connecting to cognitive control and dorsal attention regions, and ventral precuneus connecting across all subnetworks. Additionally, retrosplenial cortex showed increased connectivity across subnetworks. We suggest that connectivity from dorsal posterior midline regions is critical for the integration of external information with internal memory that facilitates long-term memory guided attention.

Smoking status affects cognitive, emotional and neural-connectivity response to distress-inducing auditory feedback

BackgroundAn important motive for cigarette smoking and impediment to cessation success is the avoidance of affective distress. Low levels of distress tolerance have been linked to smoking behavior, cessation history, smoking characteristics, and risk of recurrence among people who smoke. A better understanding of the neural mechanisms underlying distress sensitivity could inform approaches to help reduce avoidance of affective distress during smoking cessation. Previously among healthy participants, low distress tolerance on an MRI version of the Paced Auditory Serial Addition Task (PASAT-M), which induces distress via negative auditory feedback, was associated with larger differences in task-based functional connectivity (TBFC) between the auditory seed region and the anterior insula. MethodsHere, we tested differences in task performance and TBFC during affective distress among people who smoke (Smoke; n = 31) and people who quit smoking (Ex-smoke; n = 31). ResultsSmoke had poorer task accuracy and reported a steeper increase in negative mood from the easy to distress blocks. Smoke had a larger difference in connectivity (distress > easy condition) between the auditory seed region and the left inferior frontal gyrus and right anterior insula. Additionally, task accuracy positively correlated with the difference in connectivity (distress > easy condition) with the left inferior frontal gyrus and the right anterior insula among Smoke but not Ex-smoke. ConclusionsThese results are consistent with the idea that people who smoke are more sensitive to cognitive-affective distress and that the inferior frontal gyrus and anterior insula play important roles in the regulation of distress.

Task-based functional connectivity reveals aberrance with the salience network during emotional interference in late-life depression

Objectives Late-life depression (LLD) is a common and debilitating disorder. Previously, resting-state studies have revealed abnormal functional connectivity (FC) of brain networks in LLD. Since LLD is associated with emotional-cognitive control deficits, the aim of this study was to compare FC of large-scale brain networks in older adults with and without a history of LLD during a cognitive control task with emotional stimuli. Methods Cross-sectional case-control study. Twenty participants diagnosed with LLD and 37 never-depressed adults 60–88 years of age underwent functional magnetic resonance imaging during an emotional Stroop task. Network-region-to-region FC was assessed with seed regions in the default mode, the frontoparietal, the dorsal attention, and the salience networks. Results FC between salience and sensorimotor network regions and between salience and dorsal attention network regions were reduced in LLD patients compared to controls during the processing of incongruent emotional stimuli. The normally positive FC between these networks were negative in LLD patients and inversely correlated with vascular risk and white matter hyperintensities. Conclusions Emotional-cognitive control in LLD is associated with aberrant functional coupling between salience and other networks. This expands on the network-based LLD model and proposes the salience network as a target for future interventions.

Task-based functional connectivity identifies two segregated networks underlying intentional action

While much of motor behavior is automatic, intentional action is necessary for the selection and initiation of controlled motor acts and is thus an essential part of goal-directed behavior. Neuroimaging studies have shown that self-generated action implicates several dorsal and ventral frontoparietal areas. However, knowledge of the functional coupling between these brain regions during intentional action remains limited. We here studied brain activations and functional connectivity (FC) of thirty right-handed healthy participants performing a finger pressing task instructed to use a specific finger (externally-triggered action) or to select one of four fingers randomly (internally-generated action). Participants performed the task in alternating order either with their dominant right hand or the left hand. Consistent with previous studies, we observed stronger involvement of posterior parietal cortex and premotor regions when contrasting internally-generated with externally-triggered action. Interestingly, this contrast also revealed significant engagement of medial occipitotemporal regions including the left lingual and right fusiform gyrus. Task-based FC analysis identified increased functional coupling among frontoparietal regions as well as increased and decreased coupling between occipitotemporal regions, thus differentiating between two segregated networks. When comparing results of the dominant and nondominant hand we found less activation, but stronger connectivity for the former, suggesting increased neural efficiency when participants use their dominant hand. Taken together, our results reveal that two segregated networks that encompass the frontoparietal and occipitotemporal cortex contribute independently to intentional action.

Intolerance of uncertainty and functional connectivity of the anterior insula during anticipation of unpredictable reward.

Individuals with high intolerance of uncertainty (IU) tend to display maladaptive cognitive, behavioral, physiological, and/or neural responses during anticipation of uncertain or ambiguous outcomes, both positive and negative in valence. Importantly, high IU has been proposed as a key transdiagnostic phenotypic risk factor for the onset and maintenance of several psychiatric disorders. Within the context of reward processing, high IU has been related to dysfunctional reward anticipation, which may be mediated by hyperactive anterior insula (AIC) response to uncertainty. The present study further investigated the relationship between the AIC and IU by examining the association between individual differences in IU and task-based functional connectivity of the right AIC using functional magnetic resonance imaging (fMRI). Participants (N=171) completed a self-report measure of IU and a reward anticipation task during fMRI. Generalized psychophysiological interaction (gPPI) analyses were performed with a seed in the right AIC. In the U-threat model, we found that greater self-reported levels of IU were correlated with increased functional connectivity between the right AIC and the dorsal anterior cingulate cortex (dACC) and the right dorsolateral prefrontal cortex (dlPFC). In the P-threat model, we did not find these associations, perhaps indicating that they may be more robust during uncertainty. These preliminary findings suggest that parts of salience and central executive control networks may be impacted by and underlie the expression of IU. Future studies should examine the generalizability of these findings to clinical populations and investigate how disruption of these functional networks may contribute to psychopathology.

Connectome-based predictive modelling of cognitive reserve using task-based functional connectivity.

Cognitive reserve supports cognitive function in the presence of pathology or atrophy. Functional neuroimaging may enable direct and accurate measurement of cognitive reserve which could have considerable clinical potential. The present study aimed to develop and validate a measure of cognitive reserve using task-based fMRI data that could then be applied to independent resting-state data. Connectome-based predictive modelling with leave-one-out cross-validation was applied to predict a residual measure of cognitive reserve using task-based functional connectivity from the Cognitive Reserve/Reference Ability Neural Network studies (n = 220, mean age = 51.91 years, SD = 17.04 years). This model generated summary measures of connectivity strength that accurately predicted a residual measure of cognitive reserve in unseen participants. The theoretical validity of these measures was established via a positive correlation with a socio-behavioural proxy of cognitive reserve (verbal intelligence) and a positive correlation with global cognition, independent of brain structure. This fitted model was then applied to external test data: resting-state functional connectivity data from The Irish Longitudinal Study on Ageing (TILDA, n = 294, mean age = 68.3 years, SD = 7.18 years). The network-strength predicted measures were not positively associated with a residual measure of cognitive reserve nor with measures of verbal intelligence and global cognition. The present study demonstrated that task-based functional connectivity data can be used to generate theoretically valid measures of cognitive reserve. Further work is needed to establish if, and how, measures of cognitive reserve derived from task-based functional connectivity can be applied to independent resting-state data.

Evidence from an fMRI study that dessert-flavored e-cigarettes engage taste-related, but not smoking-related, brain circuitry for female daily smokers.

Regulations limiting the sale of flavored e-cigarette products are controversial for their potential to interfere with e-cigarette use as a cessation aid in addition to curbing youth use. Limited research suggests that flavor might enhance the addictive potential of e-cigarettes; however, the acute effects of flavored aerosols on brain function among humans have not been assessed. The present study aimed to isolate and compare the neural substrates of flavored and unflavored e-cigarette aerosols on brain function among nine female daily smokers. Participants inhaled aerosolized e-liquid with 36 mg/mL of nicotine with and without a strawberry-vanilla flavor while undergoing functional magnetic resonance imaging. We used general linear modeling to compare whole-brain mean neural activation and seed-to-voxel task-based functional connectivity between the flavored and unflavored inhalation runs. Contrary to our hypothesis, the flavored aerosol was associated with weaker activation than the unflavored aerosol in the brain stem and bilateral parietal-temporal-occipital region of the cortex. Instead, the flavor engaged taste-related brain regions while suppressing activation of the neural circuits typically engaged during smoking and nicotine administration. Alternatively, functional connectivity between subcortical dopaminergic brain seeds and cortical brain regions involved in motivation and reward salience were stronger during the flavored compared to unflavored aerosol run. The findings suggest that fruity and dessert-flavored e-cigarettes may dampen the reward experience of aerosol inhalation for smokers who initiate e-cigarette use by inhibiting activation of dopaminergic brain circuits. These preliminary findings may have implications for understanding how regulations on flavored e-cigarettes might impact their use as cessation aids. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Dysconnectivity between the anterior insula and the dorsal anterior cingulate cortex during an emotion go/nogo paradigm is associated with aggressive behaviors in male schizophrenia patients

This study aimed to investigate the association between past-reported violent/aggressive behaviors and brain functional connectivity in male patients suffering from schizophrenia using a task modeling the interaction between negative emotion processing and response inhibition. Forty-four male patients with schizophrenia and twenty-two healthy male controls performed an emotional go/no-go task using angry and neutral faces during a functional magnetic resonance imaging session. Generalized psycho-physiological interaction was conducted to explore task-based functional connectivity and a negative binomial regression was used to evaluate the relationship between neural alterations and violent/aggressive behaviors. Regions involved in response inhibition and emotion regulation, such as the anterior insula, dorsal anterior cingulate cortex (dACC) and dorsolateral prefrontal cortex (DLPFC), were used as seed regions. During emotion-related response inhibition, patients with schizophrenia displayed altered connectivity between the anterior insula and amygdala, the DLPFC and lateral orbitofrontal cortex (OFC), as well as the anterior insula and the dACC when compared to healthy individuals. The latter was negatively associated with aggressive behaviors in participants with schizophrenia (Wald χ2 = 9.51; p < 0.05, p-FDR corrected). Our results highlight alterations in functional connectivity in brain regions involved in cognitive control and emotion processing which are associated with aggressive behaviors in schizophrenia.

Investigating cognitive flexibility deficit in schizophrenia using task-based whole-brain functional connectivity.

Cognitive flexibility is a core cognitive control function supported by the brain networks of the whole-brain. Schizophrenic patients show deficits in cognitive flexibility in conditions such as task-switching. A large number of neuroimaging studies have revealed abnormalities in local brain activations associated with deficits in cognitive flexibility in schizophrenia, but the relationship between impaired cognitive flexibility and the whole-brain functional connectivity (FC) pattern is unclear. We investigated the task-based functional connectivity of the whole-brain in patients with schizophrenia and healthy controls during task-switching. Multivariate pattern analysis (MVPA) was utilized to investigate whether the FC pattern can be used as a feature to discriminate schizophrenia patients from healthy controls. Graph theory analysis was further used to quantify the degrees of integration and segregation in the whole-brain networks to interpret the different reconfiguration patterns of brain networks in schizophrenia patients and healthy controls. The results showed that the FC pattern classified schizophrenia patients and healthy controls with significant accuracy. Moreover, the altered whole-brain functional connectivity pattern was driven by a lower degree of network integration and segregation in schizophrenia, indicating that both global and local information transfers at the entire-network level were less efficient in schizophrenia patients than in healthy controls during task-switching processing. These results investigated the group differences in FC profiles during task-switching and not only elucidated that FC patterns are changed in schizophrenic patients, suggesting that task-based FC could be used as a potential neuromarker to discriminate schizophrenia patients from healthy controls in cognitive flexibility but also provide increased insight into the brain network organization that may contribute to impaired cognitive flexibility.

Functional connectome stability and optimality are markers of cognitive performance.

Patterns of whole-brain fMRI functional connectivity, or connectomes, are unique to individuals. Previous work has identified subsets of functional connections within these patterns whose strength predicts aspects of attention and cognition. However, overall features of these connectomes, such as how stable they are over time and how similar they are to a group-average (typical) or high-performance (optimal) connectivity pattern, may also reflect cognitive and attentional abilities. Here, we test whether individuals who express more stable, typical, optimal, and distinctive patterns of functional connectivity perform better on cognitive tasks using data from three independent samples. We find that individuals with more stable task-based functional connectivity patterns perform better on attention and working memory tasks, even when controlling for behavioral performance stability. Additionally, we find initial evidence that individuals with more typical and optimal patterns of functional connectivity also perform better on these tasks. These results demonstrate that functional connectome stability within individuals and similarity across individuals predicts individual differences in cognition.