Neural Activity Prior to Problem Presentation Predicts Subsequent Solution by Sudden Insight

Insight occurs when problem solutions arise suddenly and seem obviously correct, and is associated with an ‘‘Aha!’’ experience. Prior theorizing concerning preparation that facilitates insight focused on solvers’ problem-specific knowledge. We hypothesized that a distinct type of mental preparation, manifested in a distinct brain state, would facilitate insight problem solving independently of problem-specific knowledge. Consistent with this hypothesis, neural activity during a preparatory interval before subjects saw verbal problems predicted which problems they would subsequently solve with, versus without, self-reported insight. Specifically, electroencephalographic topography and frequency (Experiment 1) and functional magnetic resonance imaging signal (Experiment 2) both suggest that mental preparation leading to insight involves heightened activity in medial frontal areas associated with cognitive control and in temporal areas associated with semantic processing. The results for electroencephalographic topography suggest that noninsight preparation, in contrast, involves increased occipital activity consistent with an increase in externally directed visual attention. Thus, general preparatory mechanisms modulate problem-solving strategy. When Louis Pasteur said, ‘‘Chance favors only the prepared mind,’’ he was likely referring to preparation for the sort of sudden illumination that enables one to solve a difficult problem or reinterpret a situation in a new light (Wallas, 1926). Psychologists later called this type of sudden comprehension insight (Smith & Kounios, 1996; Sternberg & Davidson, 1995), a phenomenon associated with performance on tests of intelligence and creativity (Ansburg & Hill, 2003; Davidson, 1995). Although insights pop into awareness unexpectedly, or even unbidden (Kvavilashvili & Mandler, 2004; Metcalfe & Wiebe, 1987; Smith & Kounios, 1996), Pasteur apparently believed that some form of preparation facilitates insight. One type of preparation involves studying a problem or relevant background information (Seifert, Meyer, Davidson, Patalano, & Yaniv, 1995; Wallas, 1926). Such study is obviously helpful, but probably facilitates problem solving by both insight and noninsight analytic processing. We hypothesized another type of preparation, one that does not depend on information related to specific problems, but that biases a person toward processing that facilitates solution by insight. Here, we demonstrate that preparation for problem solving can be associated with distinct brain states, one biasing toward solution with insight, the other biasing toward solution without insight. We examined neural activity associated with subjects’ preparation immediately prior to the presentation of each problem and found that the spatial distribution and oscillatory frequency of this activity predicts whether the problem that follows will be solved with insight or noninsight processing, as marked by the presence or absence of an ‘‘Aha!’’ experience. Insight has typically been studied by comparing performance on insight problems, which are often solved with an ‘‘Aha!’’ experience, with performance on noninsight problems, which are usually solved without an ‘‘Aha!’’ (Mayer, 1995; Weisberg, 1995). Unfortunately, such classification is not definitive, because any particular problem could be solved with or without insight (Bowden, Jung-Beeman, Fleck, & Kounios, 2005). Instead, in the present study, we used each subject’s trial-by-trial judgments of whether each solution became available incrementally or as a sudden insight to classify solutions to individual Address correspondence to John Kounios, Department of Psychology, Drexel University, MS 626, 245 N. 15th St., Philadelphia, PA 191021192, e-mail: [email protected], or to Mark Jung-Beeman, Department of Psychology and Cognitive Brain Mapping Group, Northwestern University, 2029 Sheridan Rd., Evanston, IL 602082710, e-mail: [email protected]. PSYCHOLOGICAL SCIENCE 882 Volume 17—Number 10 Copyright r 2006 Association for Psychological Science problems as resulting from insight or noninsight processing. Using this approach, previous studies have demonstrated unique patterns of behavioral results (Bowden & Jung-Beeman, 2003a) and neural activity (Jung-Beeman et al., 2004) associated with insight versus noninsight solutions. For several reasons, we have inferred that these self-reported ‘‘Aha!’’ experiences reflect the sudden conscious availability of a solution rather than some ancillary process. For example, (a) the associated neural activity, a sudden burst of gamma-band oscillatory activity in the right anterior superior temporal gyrus, does not reflect subjects’ affective or surprise reactions following solutions, because the onset of this activity coincides with, rather than follows, the conscious availability of the solution; (b) task-related activity occurs in the same region when people first start processing a problem, before they experience any solutionrelated emotional response (Jung-Beeman et al., 2004); and (c) this region is a polymodal association area that has not been implicated in affective or novelty processing (Jung-Beeman, 2005). In two experiments, using electroencephalography (EEG) and functional magnetic resonance imaging (fMRI), we assessed neural activity as people prepared to solve each problem in a series. We examined activity prior to the presentation of each problem in order to assess patterns independent of specific problems and their difficulty. Experiment 1 focused on EEG power within the alpha (8–13 Hz) frequency band. Alpha, the brain’s dominant rhythm (Shaw, 2003), reflects cortical deactivation and is inversely related to hemodynamic and metabolic measures of neural activity (Cook, O’Hara, Uijtdehaage, Mandelkern, & Leuchter, 1998; Cooper, Croft, Dominey, Burgess, & Gruzelier, 2003; Goldman, Stern, Engel, & Cohen, 2002; Laufs et al., 2003; Ray & Cole, 1985; Worden, Foxe, Wang, & Simpson, 2000). The topographic distribution of alpha across the scalp therefore mirrors the spatial distribution of neural activity (Pfurtscheller & Lopes da Silva, 1999). We focused on the lowalpha frequency band (8–10 Hz), because high alpha (10–13 Hz) is typically dominated by an occipital alpha rhythm reflecting gating of visual information (Gevins & Smith, 2000). Effects were also found in the gamma band (> 30 Hz), but could not be reliably distinguished from electromyograph artifact, so they are not discussed in this report.