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Large-scale reconfiguration of connectivity patterns among attentional networks during context-dependent adjustment of cognitive control.

ABSTRACT: The ability to adjust our behavior flexibly depending on situational demands and changes in the environment is an important characteristic of cognitive control. Previous studies have proved that this type of adaptive control plays a crucial role in selective attention, but have barely explored whether and how attentional networks support adaptive control. In the present study, a Stroop task with a different proportion of incongruent trials was used to investigate the brain activity and connectivity of six typical attentional control networks (i.e., the fronto-parietal network (FPN), cingulo-opercular network (CON), default mode network (DMN), dorsal attention network (DAN), and ventral attention network/salience network (VAN/SN)) in the environment with changing control demand. The behavioral analysis indicated a decreased Stroop interference (incongruent vs. congruent trial response time [RT]) with the increase in the proportion of incongruent trials within a block, indicating that cognitive control was improved there. The fMRI data revealed that the attenuate Stroop interference was accompanied by the activation of frontal and parietal regions, such as bilateral dorsolateral prefrontal cortex and anterior cingulate cortex. Crucially, the improved cognitive control induced by the increased proportion of incongruent trials was associated with the enhanced functional connectivity within the five networks, and a greater connection between CON with the DAN/SN, and between DMN with the CON/DAN/SN. Meanwhile, however, the functional coupling between the FPN and VAN was decreased. These results suggest that flexible regulations of cognitive control are implemented by the large-scale reconfiguration of connectivity patterns among the attentional networks.

SUBMITTER: Li Y

PROVIDER: S-EPMC8288082 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Mindfulness has been described as an orienting of attention to the present moment, with openness and compassion. Individuals displaying high trait mindfulness exhibit this tendency as a more permanent personality attribute. Given the numerous physical and mental health benefits associated with mindfulness, there is a great interest in understanding the neural substrates of this trait. The purpose of the current research was to examine how individual differences in trait mindfulness associated with functional connectivity in five resting-state networks related to cognition and attention: the default mode network (DMN), the salience network (SN), the central executive network (CEN), and the dorsal and ventral attention networks (DAN and VAN). Twenty-eight undergraduate participants completed the Five-Facet Mindfulness Questionnaire (FFMQ), a self-report measure of trait mindfulness which also provides scores on five of its sub-categories (Observing, Describing, Acting with Awareness, Non-judging of Inner Experience, and Non-reactivity to Inner Experience). Participants then underwent a structural MRI scan and a 7-min resting state functional MRI scan. Resting-state data were analyzed using independent-component analyses. An analysis of covariance (ANCOVA) was performed to determine the relationship between each resting state network and each FFMQ score. These analyses indicated that: (1) trait mindfulness and its facets showed increased functional connectivity with neural regions related to attentional control, interoception, and executive function; and (2) trait mindfulness and its facets showed decreased functional connectivity with neural regions related to self-referential processing and mind wandering. These patterns of functional connectivity are consistent with some of the benefits of mindfulness-enhanced attention, self-regulation, and focus on present experience. This study provides support for the notion that non-judgmental attention to the present moment facilitates the integration of regions in neural networks that are related to cognition, attention, and sensation.

Project description:BackgroundAlthough cognitive processes such as reading and calculation are associated with reproducible cerebral networks, inter-individual variability is considerable. Understanding the origins of this variability will require the elaboration of large multimodal databases compiling behavioral, anatomical, genetic and functional neuroimaging data over hundreds of subjects. With this goal in mind, we designed a simple and fast acquisition procedure based on a 5-minute functional magnetic resonance imaging (fMRI) sequence that can be run as easily and as systematically as an anatomical scan, and is therefore used in every subject undergoing fMRI in our laboratory. This protocol captures the cerebral bases of auditory and visual perception, motor actions, reading, language comprehension and mental calculation at an individual level.Results81 subjects were successfully scanned. Before describing inter-individual variability, we demonstrated in the present study the reliability of individual functional data obtained with this short protocol. Considering the anatomical variability, we then needed to correctly describe individual functional networks in a voxel-free space. We applied then non-voxel based methods that automatically extract main features of individual patterns of activation: group analyses performed on these individual data not only converge to those reported with a more conventional voxel-based random effect analysis, but also keep information concerning variance in location and degrees of activation across subjects.ConclusionThis collection of individual fMRI data will help to describe the cerebral inter-subject variability of the correlates of some language, calculation and sensorimotor tasks. In association with demographic, anatomical, behavioral and genetic data, this protocol will serve as the cornerstone to establish a hybrid database of hundreds of subjects suitable to study the range and causes of variation in the cerebral bases of numerous mental processes.

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Large-scale reconfiguration of connectivity patterns among attentional networks during context-dependent adjustment of cognitive control.

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