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An underexplored aspect of the relationship between analogical reasoning and creativity is its phenomenology; in particular, the notion that analogical reasoning is related to insight and its associated "aha!" experience. However, the relationship between these phenomena has never been directly investigated. We adapted a set of verbal analogy stimuli for use as an insight task. Across the two experiments, participants reported stronger aha moments and greater representational change when reasoning about analogies with greater internal semantic distance, relative to those with greater internal semantic consistency. Aha strength increased linearly with changes in participants' verbal descriptions of the analogy over the course of each trial, indicating that aha experiences accompany changes in mental representation. The relationship between subjective difficulty and aha strength followed an inverted U-shaped function, with aha strength increasing with greater difficulty but dropping at the highest levels. A similar pattern was observed for the relationship between confidence and aha strength. Furthermore, participants in a more positive mood rated aha experiences as stronger. These findings provide evidence that analogical reasoning can give rise to the phenomenology of insight by triggering representational change and suggest that the affective consequences of relational reasoning may play an important role in promoting creative cognition.

To solve a new problem, people spontaneously engage multiple cognitive processes. Previous work has identified a diverse set of oscillatory components critical at different stages of creative problem solving. In this project, we use hidden state modeling to untangle the roles of oscillation processes over time as people solve puzzles. Building on earlier work, we further developed analytical methods, such as incorporating source separating techniques and identifying the optimal number of states using cross-validation. We extracted brain states characterized by spatio-spectral topographies from time-resolved EEG spectral powers. The data driven approach allowed us to infer the dynamic, trial-by-trial, state sequences, and provided a comprehensive depiction of how various oscillation components interact recurrently throughout the trial. The properties of the states suggest their dissociable cognitive functions. For example, we identified three states with dominant activation in alpha bands but having distinct spatial distributions. People were differentially engaged in these states depending on the stages (e.g., onset or response) and outcomes of the trials (solved with insight or analysis). The current approach, applicable to many tasks requiring extended trial duration, can potentially reconcile findings from previous EEG studies and drive new hypotheses to further our understanding of the complex creative process.

Temporal variability is a fundamental property of brain processes and is functionally important to human cognition. This study examined how fluctuations in neural oscillatory activity are related to problem-solving performance as one example of how temporal variability affects high-level cognition. We used volatility to assess step-by-step fluctuations of EEG spectral power while individuals attempted to solve word-association puzzles. Inspired by recent results with hidden-state modeling, we tested the hypothesis that spectral-power volatility is directly associated with problem-solving outcomes. As predicted, volatility was lower during trials solved with insight compared with those solved analytically. Moreover, volatility during prestimulus preparation for problem-solving predicted solving outcomes, including solving success and solving time. These novel findings were replicated in a separate data set from an anagram-solving task, suggesting that less-rapid transitions between neural oscillatory synchronization and desynchronization predict better solving performance and are conducive to solving with insight for these types of problems. Thus, volatility can be a valuable index of cognition-related brain dynamics. [ABSTRACT FROM AUTHOR]

An underexplored aspect of the relationship between analogical reasoning and creativity is its phenomenology; in particular, the notion that analogical reasoning is related to insight and its associated "aha!" experience. However, the relationship between these phenomena has never been directly investigated. We adapted a set of verbal analogy stimuli for use as an insight task. Across the two experiments, participants reported stronger aha moments and greater representational change when reasoning about analogies with greater internal semantic distance, relative to those with greater internal semantic consistency. Aha strength increased linearly with changes in participants' verbal descriptions of the analogy over the course of each trial, indicating that aha experiences accompany changes in mental representation. The relationship between subjective difficulty and aha strength followed an inverted U-shaped function, with aha strength increasing with greater difficulty but dropping at the highest levels. A similar pattern was observed for the relationship between confidence and aha strength. Furthermore, participants in a more positive mood rated aha experiences as stronger. These findings provide evidence that analogical reasoning can give rise to the phenomenology of insight by triggering representational change and suggest that the affective consequences of relational reasoning may play an important role in promoting creative cognition. [ABSTRACT FROM AUTHOR]

To solve a new problem, people spontaneously engage multiple cognitive processes. Previous work has identified a diverse set of oscillatory components critical at different stages of creative problem solving. In this project, we use hidden state modeling to untangle the roles of oscillation processes over time as people solve puzzles. Building on earlier work, we further developed analytical methods, such as incorporating source separating techniques and identifying the optimal number of states using cross-validation. We extracted brain states characterized by spatio-spectral topographies from time-resolved EEG spectral powers. The data driven approach allowed us to infer the dynamic, trial-by-trial, state sequences, and provided a comprehensive depiction of how various oscillation components interact recurrently throughout the trial. The properties of the states suggest their dissociable cognitive functions. For example, we identified three states with dominant activation in alpha bands but having distinct spatial distributions. People were differentially engaged in these states depending on the stages (e.g., onset or response) and outcomes of the trials (solved with insight or analysis). The current approach, applicable to many tasks requiring extended trial duration, can potentially reconcile findings from previous EEG studies and drive new hypotheses to further our understanding of the complex creative process. [ABSTRACT FROM AUTHOR]

Behavioral and neuroimaging findings indicate that distinct cognitive and neural processes underlie solving problems with sudden insight. Moreover, people with less focused attention sometimes perform better on tests of insight and creative problem solving. However, it remains unclear whether different states of attention, within individuals, influence the likelihood of solving problems with insight or with analysis. In this experiment, participants (N = 40) performed a baseline block of verbal problems, then performed one of two visual tasks, each emphasizing a distinct aspect of visual attention, followed by a second block of verbal problems to assess change in performance. After participants engaged in a center-focused flanker task requiring relatively focused visual attention, they reported solving more verbal problems with analytic processing. In contrast, after participants engaged in a rapid object identification task requiring attention to broad space and weak associations, they reported solving more verbal problems with insight. These results suggest that general attention mechanisms influence both visual attention task performance and verbal problem solving.

Issues surrounding the discreteness or continuity of cognitive processes have played a major role in experimental psychology, although there has been relatively little work that directly addresses these topics. Nevertheless, there has been a shift away from discrete models and toward continuous ones. The research reported in this article demonstrates discrete processing of information in an anagram task selected because of its similarity to insight problems, which seem subjectively to produce discrete 'illumination' during processing. The authors used speed-accuracy decomposition (SAD), a relatively new technique for investigating the time course of information processing. The results of 2 experiments indicate little or no partial information in the anagram tasks, in contrast to previous research with SAD, all of which has revealed partial information. General models of human information processing must therefore be able to account for both patterns.

Two studies used a response-signal procedure to explore the time course of source-monitoring judgments about perceived and imagined events. Ss judged whether probe words corresponded to pictures that had previously been seen or imagined or were new. Old-new recognition accuracy grew to significant levels before reality-monitoring accuracy, supporting the notion that source monitoring requires more of or a different type of information than does old-new recognition. Also, source identification accuracy developed more quickly for imagined items than for pcreeived items. This difference in time-course functions is consistent with the idea that memories for perceived and imagined events differ in the relative amounts of various types of information they include (Johnson & Raye, 1981) and that these different types of information may revive or become available to source attribution mechanisms at different rates or may be differentially salient during reality monitoring.

Dual-coding theory argues that processing advantages for concrete over abstract (verbal) stimuli result from the operation of 2 systems (i.e., imaginal and verbal) for concrete stimuli, rather than just 1 (for abstract stimuli). These verbal and imaginal systems have been linked with the left and right hemispheres of the brain, respectively. Context-availability theory argues that concreteness effects result from processing differences in a single system. The merits of these theories were investigated by examining the topographic distribution of event-related brain potentials in 2 experiments (lexical decision and concrete-abstract classification). The results were most consistent with dual-coding theory. In particular, different scalp distributions of an N400-like negativity were elicited by concrete and abstract words.

Are sentences verified by a lone computational mechanism, or does this mechanism race in parallel with a generally faster search of semantic memory? Rejecting either the single- or dual-process account would clarify whether semantic memory is structured, or is a relatively unstructured (computational) system. This study examined verification reaction-time (RT) distributions for a dissociation between fast and slow RTs due to the manipulation of semantic variables. A race between a search and a generally slower computational process should yield a RT distribution whose fastest RTs are usually determined by the search and whose slowest RTs are usually determined by computation. If a manipulation affects these 2 processes differently, then fast and slow RTs will be differentially affected. Results from 3 verification experiments support this view. Other results suggest even greater process complexity.

A study using event-related brain potentials (ERP) to study semantic verification was conducted. Of particular interest was the N400 negative component. Twenty four subjects participated in the two experiments conducted. Results indicated that the N400 measured retrieval mechanisms of semantic variables. Reaction time is influenced by semantic verification processes.

Brain age prediction based on imaging data and machine learning (ML) methods has great potential to provide insights into the development of cognition and mental disorders. Though different ML models have been proposed, a systematic comparison of ML models in combination with imaging features derived from different modalities is still needed. In this study, we evaluate the prediction performance of 36 combinations of imaging features and ML models including deep learning. We utilize single and multimodal brain imaging data including MRI, DTI, and rs‐fMRI from a large data set with 839 subjects. Our study is a follow‐up to the initial work (Liang et al., 2019. Human Brain Mapping) to investigate different analytic strategies to combine data from MRI, DTI, and rs‐fMRI with the goal to improve brain age prediction accuracy. Additionally, the traditional approach to predicting the brain age gap has been shown to have a systematic bias. The potential nonlinear relationship between the brain age gap and chronological age has not been thoroughly tested. Here we propose a new method to correct the systematic bias of brain age gap by taking gender, chronological age, and their interactions into consideration. As the true brain age is unknown and may deviate from chronological age, we further examine whether various levels of behavioral performance across subjects predict their brain age estimated from neuroimaging data. This is an important step to quantify the practical implication of brain age prediction. Our findings are helpful to advance the practice of optimizing different analytic methodologies in brain age prediction. [ABSTRACT FROM AUTHOR]

This study examined the effects of acute stress on creative problem-solving. Thirty-five male participants underwent stress induction via the Trier Social Stress Test; another 35 male participants engaged in a comparable, but less stressful, control task. Subsequently, they all took the Alternative Uses Test (AUT) and the Remote Associates Test (RAT), both of which are standard creative problem-solving tasks. Heart rate (HR) and salivary cortisol were recorded at regular intervals. Compared to controls, stressed participants responded with higher HR and salivary cortisol and reported more negative affect. A comparison of the effects of acute stress on two forms of creative problem-solving tasks, convergent and divergent problem-solving, showed stress-related reductions in the flexibility of solving. These effects were manifested according to the nature of the tasks: in convergent solving, stress induced faster, but less accurate responding; in divergent solving, stress reduced the flexibility of solution production, resulting in less variety of solutions. [ABSTRACT FROM AUTHOR]

Research based on construal level theory (CLT) suggests that thinking about the distant future can prime people to solve problems by insight (i.e., an “aha” moment) while thinking about the near future can prime them to solve problems analytically. In this study, we used a novel method to elucidate the time-course of temporal priming effects on creative problem solving. Specifically, we used growth-curve analysis (GCA) to examine the time-course of priming while participants solved a series of brief verbal problems. Participants were tested in two counterbalanced sessions in a within-subject experimental design; one session featured near-future priming and the other featured far-future priming. Our results suggest high-level construal may temporarily enhance analytical thinking; far-future priming caused transient facilitation of analytical solving while near-future priming induced weaker, transient facilitation of insightful solving. However, this effect is short-lived; priming produced no significant differences in the total number of insights and analytical solutions. Given the fleeting nature of these effects, future studies should consider implementing methodology that allows for aspects of the time-course of priming effects to be examined. A method such as GCA may reveal mild effects that would be otherwise missed using other types of analyses. [ABSTRACT FROM AUTHOR]

Research on creative cognition reveals a fundamental disagreement about the nature of creative thought, specifically, whether it is primarily based on automatic, associative (Type-1) or executive, controlled (Type-2) processes. We hypothesized that Type-1 and Type-2 processes make differential contributions to creative production that depend on domain expertise. We tested this hypothesis with jazz pianists whose expertise was indexed by the number of public performances given. Previous fMRI studies of musical improvisation have reported that domain expertise is characterized by deactivation of the right-dorsolateral prefrontal cortex (r-DLPFC), a brain area associated with Type-2 executive processing. We used anodal, cathodal, and sham transcranial direct current stimulation (tDCS) applied over r-DLPFC with the reference electrode on the contralateral mastoid (1.5 mA for 15 min, except for sham) to modulate the quality of the pianists' performances while they improvised over chords with drum and bass accompaniment. Jazz experts rated each improvisation for creativity, esthetic appeal, and technical proficiency. There was no main effect of anodal or cathodal stimulation on ratings compared to sham; however, a significant interaction between anodal tDCS and expertise emerged such that stimulation benefitted musicians with less experience but hindered those with more experience. We interpret these results as evidence for a dual-process model of creativity in which novices and experts differentially engage Type-1 and Type-2 processes during creative production. [ABSTRACT FROM AUTHOR]

How accurate are insights compared to analytical solutions? In four experiments, we investigated how participants' solving strategies influenced their solution accuracies across different types of problems, including one that was linguistic, one that was visual and two that were mixed visual-linguistic. In each experiment, participants' self-judged insight solutions were, on average, more accurate than their analytic ones. We hypothesised that insight solutions have superior accuracy because they emerge into consciousness in an all-or-nothing fashion when the unconscious solving process is complete, whereas analytic solutions can be guesses based on conscious, prematurely terminated, processing. This hypothesis is supported by the finding that participants' analytic solutions included relatively more incorrect responses (i.e., errors of commission) than timeouts (i.e., errors of omission) compared to their insight responses. [ABSTRACT FROM PUBLISHER]