Common and specific neural correlates underlying insight and ordinary problem solving

Lin, Jiabao; Yang, Sihua; Cui, Xuan; Xiang, Yu‐Tao; Xie, Jiushu; Chen, Yajue; Huang, Ruiwang; Mo, Lei

doi:10.1007/s11682-020-00337-z

Cited by 11 publications

(22 citation statements)

References 72 publications

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“…While in the high insight task, participants needed to remove an isolated character from the given character in order to obtain the target character. Previous studies have proved that the low and high insightful Mandarin character chunk decomposition tasks can successfully induce corresponding insight feelings, and details of the tasks can be found in these studies ( Lin et al, 2019 , 2020 ). Notably, the two insight tasks were together used to measure the individual differences of IPS.…”

Section: Methodsmentioning

confidence: 92%

“…Finally, we used a seed-based approach to further examine the FC patterns of each cluster founded in DC analysis. Based on previous studies ( Wei et al, 2014 ; Huang et al, 2015 ; Tang et al, 2015 ; Benedek et al, 2018 ; Lin et al, 2020 ), we predicted that hub regions, such as lateral or medial prefrontal cortex, may play a critical role in IPS, and IPS may be closely related to activations of the DMN.…”

Section: Introductionmentioning

confidence: 98%

“…experience). It has been suggested that IPS is associated with brain functions of set-shifting, mental restructuring, forming new associations, and emotion processing ( Tik et al, 2018 ; Lin et al, 2020 ; Li et al, 2022 ). However, the neural substrates of individual difference in solving insightful problems remain elusive.…”

Section: Introductionmentioning

confidence: 99%

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Altered Brain Connectivity Patterns of Individual Differences in Insightful Problem Solving

Lin

Chen

Xie

et al. 2022

Front. Behav. Neurosci.

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Insightful problem solving (IPS) attracts widespread attention in creative thinking domains. However, the neural underpinnings of individual differences in IPS are still unclear. The purpose of this research was to investigate inherent full-brain connectivity patterns at voxel-level in IPS. Sixty-two healthy participants were enrolled in the study. We used a voxelwise full-brain network measurement, degree centrality (DC), to depict the characteristics of cerebral network involved in individual differences in IPS. For each participant, we employed a chunk decomposition paradigm, using Mandarin characters as stimuli, to estimate the individual differences in IPS. Results showed that DC in the inferior frontal gyrus, and the middle frontal gyrus/precentral gyrus positively correlated with IPS, while the anterior cingulate cortex, and the brainstern/cerebellum/thalamus exhibited negative correlations with IPS. Using each cluster above as a seed, we performed seed-based functional connectivity analysis further. Results showed that IPS was mainly involved in the default mode network, containing the key regions of precuneus and medial prefrontal cortex. All in all, this research may shed new lights on understanding the neural underpinnings of individual differences in IPS.

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Section: Methodsmentioning

confidence: 92%

Section: Introductionmentioning

confidence: 98%

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Altered Brain Connectivity Patterns of Individual Differences in Insightful Problem Solving

Lin

Chen

Xie

et al. 2022

Front. Behav. Neurosci.

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“…Problem solving is the capacity to achieve a goal through a sequence of cognitive operations (step by step) or insight [ 19 ]. Ordinary problem solving is a way to solve problems based on previous experience and uses well-known solutions.…”

Section: Introductionmentioning

confidence: 99%

“…Ordinary problem solving is regulated by the Frontoparietal Cognitive Control Network, which includes the middle frontal gyrus, inferior frontal gyrus, and inferior parietal lobule, and it involves a greater activation of Default Mode Network (DMN). Insight in problem solving is regulated by the same areas that regulate the ordinary problem solving with the addition of the anterior cingulate cortex and temporoparietal junction, and it involves a higher activation of visuospatial attention and visual perception areas [ 19 ].…”

Section: Introductionmentioning

confidence: 99%

Higher-Level Executive Functions in Healthy Elderly and Mild Cognitive Impairment: A Systematic Review

Corbo

Casagrande

2022

JCM

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Mild Cognitive Impairment (MCI) is a clinical syndrome characterized by a moderate decline in one or more cognitive functions with a preserved autonomy in daily life activities. MCI exhibits cognitive, behavioral, psychological symptoms. The executive functions (EFs) are key functions for everyday life and physical and mental health and allow for the behavior to adapt to external changes. Higher-level executive functions develop from basic EFs (inhibition, working memory, attentional control, and cognitive flexibility). They are planning, reasoning, problem solving, and fluid intelligence (Gf). This systematic review investigates the relationship between higher-level executive functions and healthy and pathological aging, assuming the role of executive functions deficits as a predictor of cognitive decline. The systematic review was conducted according to the PRISMA Statement. A total of 73 studies were identified. The results indicate that 65.8% of the studies confirm significant EFs alterations in MCI (56.8% planning, 50% reasoning, 100% problem solving, 71.4% fluid intelligence). These results seem to highlight a strong prevalence of higher-level executive functions deficits in MCI elderly than in healthy elderly.

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Uncovering neural distinctions and commodities between two creativity subsets: A meta‐analysis of fMRI studies in divergent thinking and insight using activation likelihood estimation

Kuang

Chen

Shi

et al. 2022

Human Brain Mapping

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The dual‐process theory that two different systems of thought coexist in creative thinking has attracted considerable attention. In the field of creative thinking, divergent thinking (DT) is the ability to produce multiple solutions to open‐ended problems in a short time. It is mainly considered an associative and fast process. Meanwhile, insight, the new and unexpected comprehension of close‐ended problems, is frequently marked as a deliberate and time‐consuming thinking process requiring concentrated effort. Previous research has been dedicated to revealing their separate neural mechanisms, while few studies have compared their differences and similarities at the brain level. Therefore, the current study applied Activation Likelihood Estimation to decipher common and distinctive neural pathways that potentially underlie DT and insight. We selected 27 DT studies and 30 insight studies for retrospective meta‐analyses. Initially, two single analyses with follow‐up contrast and conjunction analyses were performed. The single analyses showed that DT mainly involved the inferior parietal lobe (IPL), cuneus, and middle frontal gyrus (MFG), while the precentral gyrus, inferior frontal gyrus (IFG), parahippocampal gyrus (PG), amygdala (AMG), and superior parietal lobe were engaged in insight. Compared to insight, DT mainly led to greater activation in the IPL, the crucial part of the default mode network. However, insight caused more significant activation in regions related to executive control functions and emotional responses, such as the IFG, MFG, PG, and AMG. Notably, the conjunction analysis detected no overlapped areas between DT and insight. These neural findings implicate that various neurocognitive circuits may support DT and insight.

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Common and specific neural correlates underlying insight and ordinary problem solving

Cited by 11 publications

References 72 publications

Altered Brain Connectivity Patterns of Individual Differences in Insightful Problem Solving

Altered Brain Connectivity Patterns of Individual Differences in Insightful Problem Solving

Higher-Level Executive Functions in Healthy Elderly and Mild Cognitive Impairment: A Systematic Review

Uncovering neural distinctions and commodities between two creativity subsets: A meta‐analysis of fMRI studies in divergent thinking and insight using activation likelihood estimation

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