Memory Suppression Ability can be Robustly Predicted by the Internetwork Communication of Frontoparietal Control Network

Everything you ever wanted to know about the Think/No-Think task, but forgot to ask

The Think/No-Think (TNT) task has just celebrated 20 years since its inception, and its use has been growing as a tool to investigate the mechanisms underlying memory control and its neural underpinnings. Here, we present a theoretical and practical guide for designing, implementing, and running TNT studies. For this purpose, we provide a step-by-step description of the structure of the TNT task, methodological choices that can be made, parameters that can be chosen, instruments available, aspects to be aware of, systematic information about how to run a study and analyze the data. Importantly, we provide a TNT training package (as Supplementary Material), that is, a series of multimedia materials (e.g., tutorial videos, informative HTML pages, MATLAB code to run experiments, questionnaires, scoring sheets, etc.) to complement this method paper and facilitate a deeper understanding of the TNT task, its rationale, and how to set it up in practice. Given the recent discussion about the replication crisis in the behavioral sciences, we hope that this contribution will increase standardization, reliability, and replicability across laboratories.

Disrupted network communication predicts mild cognitive impairment in end-stage renal disease: an individualized machine learning study based on resting-state fMRI

End-Stage Renal Disease (ESRD) is known to be associated with a range of brain injuries, including cognitive decline. The purpose of this study is to investigate the functional connectivity (FC) of the resting-state networks (RSNs) through resting state functional magnetic resonance imaging (MRI), in order to gain insight into the neuropathological mechanism of ESRD. A total of 48 ESRD patients and 49 healthy controls underwent resting-state functional MRI and neuropsychological tests, for which Independent Components Analysis and graph-theory (GT) analysis were utilized. With the machine learning results, we examined the connections between RSNs abnormalities and neuropsychological test scores. Combining intra/inter network FC differences and GT results, ESRD was optimally distinguished in the testing dataset, with a balanced accuracy of 0.917 and area under curve (AUC) of 0.942. Shapley additive explanations results revealed that the increased functional network connectivity between DMN and left frontoparietal network (LFPN) was the most critical predictor for ESRD associated mild cognitive impairment diagnosis. Moreover, hypoSN (salience network) was positively correlated with Attention scores, while hyperLFPN was negatively correlated with Execution scores, indicating correlations between functional disruption and cognitive impairment measurements in ESRD patients. This study demonstrated that both the loss of FC within the SN and compensatory FC within the lateral frontoparietal network coexist in ESRD. This provides a network basis for understanding the individual brain circuits and offers additional noninvasive evidence to comprehend the brain networks in ESRD.

Connectome-based prediction of eating disorder-associated symptomatology

BACKGROUND

Despite increasing knowledge on the neuroimaging patterns of eating disorder (ED) symptoms in non-clinical populations, studies using whole-brain machine learning to identify connectome-based neuromarkers of ED symptomatology are absent. This study examined the association of connectivity within and between large-scale functional networks with specific symptomatic behaviors and cognitions using connectome-based predictive modeling (CPM).

METHODS

CPM with ten-fold cross-validation was carried out to probe functional networks that were predictive of ED-associated symptomatology, including body image concerns, binge eating, and compensatory behaviors, within the discovery sample of 660 participants. The predictive ability of the identified networks was validated using an independent sample of 821 participants.

RESULTS

The connectivity predictive of body image concerns was identified within and between networks implicated in cognitive control (frontoparietal and medial frontal), reward sensitivity (subcortical), and visual perception (visual). Crucially, the set of connections in the positive network related to body image concerns identified in one sample was generalized to predict body image concerns in an independent sample, suggesting the replicability of this effect.

CONCLUSIONS

These findings point to the feasibility of using the functional connectome to predict ED symptomatology in the general population and provide the first evidence that functional interplay among distributed networks predicts body shape/weight concerns.

Amygdala-based functional connectivity mediates the relationship between thought control ability and trait anxiety

Thought control ability (TCA) refers to the ability to exclude unwanted thoughts. There has been consistent evidence on the protective effect of TCA on anxiety, that higher TCA is associated with lower anxiety. However, the underlying neural mechanism remains unclear. In this study, with a large sample (N = 495), we investigated how seed-based resting-state functional connectivity (RSFC) mediates the relationship between TCA and anxiety. Our behaviour results replicated previous findings that TCA is negatively associated with trait anxiety after controlling for gender, age, and depression. More importantly, the RSFC results revealed that TCA is negatively associated with the left amygdala - left frontal pole (LA-LFP), left amygdala - left inferior temporal gyrus (LA-LITG), and left hippocampus - left inferior frontal gyrus (LH-LIFG) connectivity. In addition, a mediation analysis demonstrated that the LA-LFP and LA-LITG connectivity in particular mediated the influence of TCA on trait anxiety. Overall, our study extends previous research by revealing the neural bases underlying the protective effect of TCA on anxiety and pinpointing specific mediating RSFC pathways. Future studies could explore whether targeted TCA training (behavioural or neural) can help alleviate anxiety.

Connectome-based individualized prediction of reciprocity propensity and sensitivity to framing: a resting-state functional magnetic resonance imaging study

BACKGROUND

The social representation theory states that individual differences in reciprocity decisions are composed of a stable central core (i.e., reciprocity propensity, RP) and a contextual-dependent periphery (i.e., sensitivity to the framing effect; SFE, the effect by how the decision is presented). However, the neural underpinnings that explain RP and SFE are still unknown.

METHOD

Here, we employed prediction and lesion models to decode resting-state functional connectivity (RSFC) of RP and SFE for reciprocity decisions of healthy volunteers who underwent RS functional magnetic resonance imaging and completed one-shot trust (give frame) and distrust (take frame) games as trustees.

RESULTS

Regarding the central core, reciprocity rates were positively associated between the give and take frame. Neuroimaging results showed that inter-network RSFC between the default-mode network (DMN; associated with mentalizing) and cingulo-opercular network (associated with cognitive control) contributed to the prediction of reciprocity under both frames. Regarding the periphery, behavioral results demonstrated a significant framing effect-people reciprocated more in the give than in the take frame. Our neuroimaging results revealed that intra-network RSFC of DMN (associated with mentalizing) contributed dominantly to the prediction of SFE.

CONCLUSION

Our findings provide evidence for distinct neural mechanisms of RP and SFE in reciprocity decisions.

Age-related intrinsic functional connectivity underlying emotion utilization

Previous studies investigated the age-related positivity effect in terms of emotion perception and management, whereas little is known about whether the positivity effect is shown in emotion utilization (EU). If yes, the EU-related intrinsic functional connectivity and its age-associated alterations remain to be elucidated. In this study, we collected resting-state functional magnetic resonance imaging data from 62 healthy older adults and 72 undergraduates as well as their self-ratings of EU. By using the connectome-based predictive modeling (CPM) method, we constructed a predictive model of the positive relationship between EU self-ratings and resting-state functional connectivity. Lesion simulation analyses revealed that the medial-frontal network, default mode network, frontoparietal network, and subcortical regions played key roles in the EU-related CPM. Older subjects showed significantly higher EU self-ratings than undergraduates, which was associated with strengthened connectivity between the left dorsolateral prefrontal cortex and bilateral frontal poles, and between the left frontal pole and thalamus. A mediation analysis indicated that the age-related EU network mediated the age effect on EU self-ratings. Our findings extend previous research on the age-related "positivity effect" to the EU domain, suggesting that the positivity effect on the self-evaluation of EU is probably associated with emotion knowledge which accumulates with age.

Knowing what you feel: Inferior frontal gyrus-based structural and functional neural patterns underpinning adaptive body awareness

BACKGROUND

Heightened body awareness (BA) is conducive for increasing understanding of bodily state and improves individuals' health and well-being. Although there has been cumulative research concentrating on the self-perceived tendency to focus on negatively valenced interoceptive sensations, the specific structural and functional neural patterns underlying BA and their role in the relationship between BA and individual well-being remain unclear.

METHODS

Voxel-based morphometry and whole brain functional connectivity analyses were conducted to examine the structural and functional neural patterns, respectively, in 686 healthy subjects. BA and subjective well-being were assessed using questionnaires.

RESULTS

BA was inversely related to gray matter volume of the right inferior frontal gyrus, opercular part (IFGoperc). Higher BA was correlated with enhanced IFGoperc-precuneus and IFGoperc-anterior supramarginal gyrus connectivities, and with decreased IFGoperc-lateral occipital cortex and IFGoperc-medial frontal cortex connectivities. The inferior frontal gyrus, triangular part (in the fronto-parietal task control network) acted as the hub that linked the sensory/somatomotor network, the default mode network, and the dorsal and ventral attention network. The IFGoperc-precuneus connectivity moderated the association between BA and subjective well-being.

LIMITATIONS

We were unable to rank all the networks by their relative importance, because the absolute weighted value in each module was not calculated.

CONCLUSION

Our findings demonstrated that BA was reflected by specific neural patterns mainly involved in cognitive-affective control, attentional and self-referential processing, as well as multisensory integration, which could offer some references for current therapies (e.g., mindfulness, yoga training) that are dedicated to solving health problems and improving individual well-being.

Reduced hippocampal-cortical connectivity during memory suppression predicts the ability to forget unwanted memories

The ability to suppress unwelcome memories is important for productivity and well-being. Successful memory suppression is associated with hippocampal deactivations and a concomitant disruption of this region's functionality. Much of the previous neuroimaging literature exploring such suppression-related hippocampal modulations has focused on the region's negative coupling with the prefrontal cortex. Task-based changes in functional connectivity between the hippocampus and other brain regions still need further exploration. In the present study, we utilize psychophysiological interactions and seed connectome-based predictive modeling to investigate the relationship between the hippocampus and the rest of the brain as 134 participants attempted to suppress unwanted memories during the Think/No-Think task. The results show that during retrieval suppression, the right hippocampus exhibited decreased functional connectivity with visual cortical areas (lingual and cuneus gyrus), left nucleus accumbens and the brain-stem that predicted superior forgetting of unwanted memories on later memory tests. Validation tests verified that prediction performance was not an artifact of head motion or prediction method and that the negative features remained consistent across different brain parcellations. These findings suggest that systemic memory suppression involves more than the modulation of hippocampal activity-it alters functional connectivity patterns between the hippocampus and visual cortex, leading to successful forgetting.

Dynamic Transitions between Neural States Are Associated with Flexible Task Switching during a Memory Task

Flexible behavior requires switching between different task conditions. It is known that such task switching is associated with costs in terms of slowed RT, reduced accuracy, or both. The neural correlates of task switching have usually been studied by requiring participants to switch between distinct task conditions that recruit different brain networks. Here, we investigated the transition of neural states underlying switching between two opposite memory-related processes (i.e., memory retrieval and memory suppression) in a memory task. We investigated 26 healthy participants who performed a think/no-think task while being in the fMRI scanner. Behaviorally, we show that it was more difficult for participants to suppress unwanted memories when a no-think was preceded by a think trial instead of another no-think trial. Neurally, we demonstrate that think-no-think switches were associated with an increase in control-related and a decrease in memory-related brain activity. Neural representations of task condition, assessed by decoding accuracy, were lower immediately after task switching compared with the nonswitch transitions, suggesting a switch-induced delay in the neural transition toward the required task condition. This suggestion is corroborated by an association between condition-specific representational strength and condition-specific performance in switch trials. Taken together, we provided neural evidence from the time-resolved decoding approach to support the notion that carryover of the previous task set activation is associated with the switching cost, leading to less successful memory suppression.

Task compliance predicts suppression-induced forgetting in a large sample

Suppression-induced forgetting (SIF) refers to a memory impairment resulting from repeated attempts to stop the retrieval of unwanted memory associates. SIF has become established in the literature through a growing number of reports built upon the Think/No-Think (TNT) paradigm. Not all individuals and not all reported experiments yield reliable forgetting, however. Given the reliance on task instructions to motivate participants to suppress target memories, such inconsistencies in SIF may reasonably owe to differences in compliance or expectations as to whether they will again need to retrieve those items (on, say, a final test). We tested these possibilities on a large (N = 497) sample of TNT participants. In addition to successfully replicating SIF, we found that the magnitude of the effect was significantly and negatively correlated with participants’ reported compliance during the No-Think trials. This pattern held true on both same- and independent-probe measures of forgetting, as well as when the analysis was conditionalized on initial learning. In contrast, test expectancy was not associated with SIF. Supporting previous intuition and more limited post-hoc examinations, this study provides robust evidence that a lack of compliance with No-Think instructions significantly compromises SIF. As such, it suggests that diminished effects in some studies may owe, at least in part, to non-compliance—a factor that should be carefully tracked and/or controlled. Motivated forgetting is possible, provided that one is sufficiently motivated and capable of following the task instructions.