Exp Brain Res (2008) 186:629–634

DOI 10.1007/s00221-008-1270-7

RESEARCH ARTICLE

Spatiotemporal cortical activation underlies mental preparation for successful riddle solving: an event-related potential study

Jiang Qiu · Hong Li · Jerwen Jou · Zhenzhen Wu · Qinglin Zhang

Received: 21 August 2007 / Accepted: 3 January 2008 / Published online: 24 January 2008© Springer-Verlag 2008

Abstract Recently, Kounios J, Frymiare JL, BowdenEM, Fleck JI, Subramaniam K, Parrish TB et al. (2006)found that the mental preparation leading to insightinvolves heightened activity in medial frontal areas andtemporal areas. In the present study, the electrophysiologi-cal correlates of successful and unsuccessful Chinese logo-griph solving (riddles in which writing characters undergoseveral changes brought about by the addition, subtraction,omission or substitution of strokes or components of thecharacters) were studied in 18 healthy subjects using high-density event-related potentials (ERPs). Results show thatthe mental preparation for successful logogriphs elicited amore positive ERP deXection than unsuccessful logogriphsfrom ¡1,000 to ¡800 ms before onset of the target logog-riphs. Dipole analysis localized the generators of the posi-tive component primarily in the anterior cingulate cortex(ACC). This result is consistent with Kounios’ view thatgeneral mental preparatory mechanisms modulate problem-solving strategy.

Keywords Problem solving · Mental preparation · Anterior cingulate cortex (ACC) · Event-related potentials (ERPs)

Introduction

Insight is a complex cognitive process that is not fullyunderstood. In the process of insight problem solving, theinitially purposeful thinking is followed by an impasse, i.e.,a state of mind in which the problem solver becomes stuck.A new idea or option will, in some cases, suddenly andunexpectedly come to mind after continued concentrationon the problem. Then the problem solver can rapidly Wnd asolution (e.g., Weisberg 1995; Smith 1996; Schooler 1995).Recently developed brain imaging techniques such as func-tional magnetic resonance imaging (fMRI) and event-related potentials (ERPs) have made it possible to recordbrain activity associated with insight problem solving. Forexample, Luo et al. (2003, 2004) recorded neural activityusing fMRI and correlated activity with cognitive insightby providing a trigger (the solution) to catalyze insightfulriddle solving processes. Results showed that insight riddlesolving was associated with activity primarily in the anteriorcingulate cortex (ACC) and the prefrontal cortex (PFC). Ina series of studies using the compound remote associatesproblem (CRA, e.g., boot, summer, ground; solutions:camp), Bowden et al. (2003, 2005) found two objectiveneural correlates of insight. fMRI results revealed anincreased signal in the right anterior superior temporalgyrus for insight but not non-insight solutions and scalpEEG recordings revealed a sudden burst of high-frequency(gamma-band) neural activity in the same region just beforeinsight, but not non-insight solutions.

Many groups have tried to use advanced brain imagingtechniques to investigate neural mechanisms underlyinginsight (e.g., Luo et al. 2003; Mai et al. 2004; Qiu et al.2006; Bowden et al. 2003, 2005). However, there are manydiYculties in analyzing insight problem solving. “Insight”occurs when one breaks unwarranted mental “Wxation”.

J. Qiu · H. Li · Q. ZhangKey Laboratory of Cognition and Personality (SWU), Ministry of Education, Chongqing, China

J. Qiu · H. Li · Z. Wu · Q. Zhang (&)School of Psychology, Southwest University, Beibei, Chongqing 400715, Chinae-mail: qiuj318@swu.edu.cn; qiuj318@yahoo.com

J. JouDepartment of Psychology and Anthropology, University of Texas-Pan American, Edinburg, TX, USA

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Additionally “insight” occurs when novel, task-relatedassociations are formed on the old nodes of concepts orcognitive skills (see Luo et al. 2003; Bowden et al. 2005).Recently, Kounios et al. hypothesized that a distinct type ofmental preparation, manifested in a distinct brain state,facilitated insight problem solving independent of speciWcproblems. In fact, they found greater neural activity forinsight than for non-insight preparation in medial frontalareas associated with cognitive control and in bilateraltemporal cortex associated with semantic processing(Kounios et al. 2006).

In the present study, a novel two-stage model using alearning-testing experimental paradigm was adopted todetermine whether neural activity prior to solving riddlespredicts subsequent success in Wnding a solution. The modelis designed to make subjects Wnd a solution on their owninitiative rather than just receive answers passively. Ourstudy adopted Chinese riddles (logogriphs), which are tradi-tionally classiWed as “insight problems”. Logogriphs inwestern countries focus on the separation and reunion of let-ters, syllables or words, while Chinese logogriphs are rid-dles in which a written character is made to undergo severalchanges brought about by the addition, subtraction, omis-sion or substitution of strokes or components of characters.Chinese characters are formed by strokes and some com-plex characters are composed of some other simple charac-ters. To solve Chinese logogriphs, the subjects are expectedto read between the lines and discover the deep meanings ofthe riddles, and they may get the answer either by restruc-turing the components of the characters to make new onesor by catching the implicit meanings the riddles intend.First, subjects learned a base logogriph with the answeroVered (learning stage), and then they were asked to solve ahomotypical logogriph (target logogriph) where the baselogogriph learned beforehand would provide heuristic infor-mation for Wnding a solution (testing stage). In the presentstudy, we were interested in the neural basis of mental prep-aration during a preparatory interval before subjects saw thetarget logogriph. We recorded and analyzed high-densityERPs elicited by logogriphs to reveal the electrophysiologi-cal correlates of the mental preparation of successful andunsuccessful insight problem solving.

Materials and methods

Subjects

Subjects were 18 junior undergraduates (9 women, 9 men)aged 19–26 years (mean age, 22.3 years) from SouthwestUniversity in China. All subjects who gave writteninformed consent, right-handed, had no history of currentor past neurological or psychiatric illness, and had normal

or corrected-to-normal vision. In addition, subjects werepaid for participating.

Experimental stimuli

From the available 180 logogriphs, we selected 150 targetlogogriphs that were prescreened by their diYculty andtheir ability to provoke interest in the subjects. Most logog-riphs were between 2 and 6 characters in length, while allanswers were a single character. The words that appeared inboth the questions and answers were of high frequency, andwere presented in the center of the screen. The characterswere presented in the Song Ti font, at size No. 16. Accord-ing to the two-stage mode, we divided the 150 logogriphsinto two groups, true- and false-matching logogriphs.

True-matching logogriphs

For each of the 75 target logogriphs, a real heuristic logo-griph (a base logogriph) was made for subjects to learn. Forexample, “you kou nan yan” ( base logogriph)vs. “you yan nan jian” ( target logogriph). Sub-jects Wrst learn the base logogriph and get heuristic infor-mation for solving the target logogriph. Based on thesuperWcial meaning, “you kou nan yan” (literally meaningbeing unable to speak even with a mouth) will Wrst be asso-ciated with a Chinese character “y8 ( literally meansmute)”. In the Chinese language, “y8” is composed of twoother characters, “kou” ( literally meaning mouth) and“yà” ( literally meaning second). In other words, whenthe character “kou” (mouth) is added to “yà”, the newlyformed character is “y8” (mute). Because the meaning ofthe riddle is being unable to speak even with a mouth, when“kou” (mouth) is added to “yà”, the meaning of the charac-ter formed (y8) is mute. Therefore the answer to the riddleis “yà”. The key point in solving the riddle is Wrst throughunderstanding the surface meaning of the riddle and thenobtaining the answer by recombining, splitting and remov-ing certain components of the Chinese characters. When thetarget logogriph appeared, subjects could easily guess theanswer of logogriph (“you yan nan jian”) because the targetlogogriph resembled the base logogriph. Based on thesuperWcial meaning, “you yan nan jian” (literally meaningbeing unable to see even with eyes) will Wrst be associatedwith a Chinese character “mang ( literally meansblind)”. In Chinese language, “mang” is composed of twoother characters, “wang” ( literally means death) and“mu” ( literally means eyes). Therefore understandingthe surface meaning of the riddle and removing certaincomponents of the Chinese character (“mu”), the answer(“wang”) would be obtained. False-matching logogriphs

For each of the remaining 75 target logogriphs, a non-heuristic logogriph was made for subjects to learn. Contrary

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to true-matching logogriphs, base logogriphs and targetlogogriphs in this group had no connection. Subjects couldnot get useful heuristic information from the base logogriphsto help solve the target logogriphs. It was often diYcult toWnd the correct answer in time and subjects seldom had an“Aha!” experience. In our design, the Wrst logogriphs in bothof the true-matching and falsely-matching trials were equallyeasy to comprehend and transferred to the second logogriph.

Experimental design

The Xow of learning and testing logogriphs in each trial isshown in Fig. 1. First, the learning logogriphs (logogriphsand answers) were presented in the center of the screen for8 s. Subjects were instructed to try to understand the logog-riphs, and press the “1” key with their right index Wngeronly if they understood it. After a 1.5 s interval duringwhich the subject was shown “+”, the test logogriph wasthen presented in the center of the screen for 4 s. Subjectswere required to guess the answers quickly according to theinformation they gained in the learning stage. Again, sub-jects were required to press the “1” key quickly with theirright index Wnger once they guessed the answer, or press nokey if they did not guess an answer. After a 1 s interval, thecorrect answer was presented in the center of the screen for2 s. At this time, subjects were asked to judge whether theguess they made was consistent to the correct answer andhereby make the corresponding response by pressing keys.Press “1” key if their own guesses were consistent to thecorrect answers, press “2” key if they did not guess the rid-dles but could understand the correct answers and pressingno key if they neither guessed the riddles nor understoodthe correct answers.

In the formal test, 140 logogriphs (70 true-matching and70 false-matching logogriphs) were divided into Wve blockswith 28 logogriphs in each block. No logogriphs wererepeated. Between the blocks, subjects rested. Subjectswere seated in a quiet room facing a screen placed 60 cmdistance from their eyes and were instructed to respond asfast and accurately as possible by pressing the correspond-ing button of the keyboard. Subjects were asked to sit stilland blink as little as possible. In addition, to identifywhether subjects experienced an “Aha!” sensation ofsurprise, we used subjective reports of the problem solvingexperience after they Wnished the experiment. Although thereports are subjective, they can indicate what problemsolving processes were engaged on a trial-by-trial basis.

ERP recording and analysis

Brain electrical activity was recorded from 64 scalp sitesusing tin electrodes mounted in an elastic cap (Brain Prod-uct), with the reference on the left and right mastoids. Thevertical electrooculogram (EOG) was recorded withelectrodes placed above and below the left eye. All inter-electrode impedance was maintained below 5 k�. The EEGand EOG were ampliWed using a 0.05–80 Hz bandpass andcontinuously sampled at 500 Hz/channel for oV-line analy-sis. Eye movement artifacts (blinks and eye movements)were rejected oVline. ERPs were analyzed before onset ofthe target logogriphs and epoch change within 1,000 mswith the baseline post-stimulus 200 ms to evaluate whetherneural activity during a preparatory interval would predicwhich problems they would subsequently successfullysolve. We also analyzed ERPs after the onset of the testlogogriphs (data not shown). EEGs of mental preparationwere separated into successful and unsuccessful logogriphgroups and averaged. As seen in the grand averaged wave-forms and topographical maps (see Fig. 2), the ERPs elic-ited by successful and unsuccessful logogriphs conditionsshowed prominent diVerences from each other. For displayof scalp topography and source localization, the diVerencewave was obtained by subtracting the averaged ERP ofunsuccessful logogriphs from the averaged ERP of success-ful logogriphs. Results showed that these diVerences weremostly large over the fronto-central scalp regions.Therefore, the following 13 electrode points were chosenfor two-way repeated measures analyses of variance(ANOVA). The ANOVA factors were response type (suc-cessful and unsuccessful logogriphs solving), and electrodesite (Fz, Cz, Pz, F1, F2, F5, F6, C3, C4, FT7, FT8, P3 andP4). Mean amplitudes in the time window of ¡800 to¡600 ms and ¡1,000 to ¡800 ms were chosen for statisti-cal analysis. P-values of ANOVA were corrected for devia-tions according to Greenhouse Geisser method.

Results

The results of behavioural and ERP data were analyzed for16 subjects (2/18 subjects were excluded because the numberof solved logogriphs was less than 20 trials). As shown in thebehavioural data, the average number of solved logogriphs(successful logogriphs) was 41 § 9 (58.6 § 12.8%), underthe true-matching condition. Under the false-matching con-dition, within the time allowed (4 s), the average number ofsolved logogriphs was 20 § 10 (28.5 § 14.2%). Therepeated-measures ANOVA indicated that the mean accu-racy rate was higher in the true-matching condition than inthe false-matching condition [F(1, 15) = 245.92, P < 0.001].In addition, results of subjective reports indicated that

Fig. 1 The Xow of learning and testing logogriphs in each trial

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subjects had a pleasant feeling of surprise or an understand-ing of how to reach the solution. This sensation wasreported to come all at once when people solved a logo-griph successfully, i.e., with insight problem solving.

As the grand average waveforms and diVerence wavemap shown in Fig. 2, we found that mental preparation ofsuccessful logogriphs elicited a more positive ERP deXec-tion than unsuccessful logogriphs from ¡1,000 to ¡800 msbefore onset of the target logogriphs. Activation wasprimarily in the midline fronto-central scalp.

Two-factors repeated measures ANOVA showed thatthe response type from ¡1000 to ¡800 ms signiWcantlyaVected ERPs such that successful logogriphs elicited amore late positive ERP deXection than unsuccessful logog-riphs [F(1,15) = 5.36, P < 0.05]. In addition, the electrodesites signiWcantly aVected ERPs [F(12, 180) = 3.71, P < 0.05].However the interaction between response and electrode

site was not signiWcant [F(12, 180) = 1.51, P > 0.05]. Inother time windows, neither the response type nor theresponse type and electrode site interaction were signiW-cant.

The dipole source analysis based on a three-shell spheri-cal head model was carried out using the BESA software(BESA, Version, 5.0, Software) on the grand averagediVerence wave between successful and unsuccessfullogogriphs (Fig. 3). Principal component analysis (PCA)was employed from ¡1,000 to ¡800 ms in which the maineVect of the response type was signiWcant. Three principalcomponents were needed to explain 92.5% (separately59.9, 26.8 and 5.8%) of the variance in the data from¡1,000 to ¡800 ms. Therefore these three dipoles wereWtted with no restriction to the direction or location ofdipole. The Wrst dipole is located approximately in the ante-rior mesial cingulate cortex (x = 1.9, y = 6.5, z = 27.9), the

Fig. 2 Top Grand average ERPs at Fz, FCz, Cz and Pz for the mental preparation of successful logogriphs (thin solid lines), unsuccessful logogriphs (dotted lines) and the diVerence wave (successful minus unsuccessful; thick solid lines). Bottom Topo-graphical maps of the voltage amplitudes for the diVerence wave from ¡860 to ¡800 ms, ¡920 to ¡860 ms and ¡980 to ¡920 ms

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second near the left anterior cingulate cortex (x = ¡14.9,y = 25.7, z = 1.4) and the third near the right parahippocam-pal gyrus (x = 6.0, y = ¡8.7, z = ¡17.1). This model bestexplains the data and accounts for most of the variance witha residual variance (RV) of 12.8% at the peak of activity(¡850 ms) of these dipoles. The validities of this modelwere tested through the following steps. First, the display ofthe residual maps in the time window (¡1,000 to ¡800 ms)showed no further dipolar activity; second, no other dipolescould be Wtted in the investigated time window by compar-ing the solution with other plausible alternatives (e.g., bilat-erally symmetric dipoles). These tests suggest that themodel explained the data in the best manner for the timewindow. However, due to inherent limitations of sourcelocalization, the brain areas implicated by source localiza-tion are only tentative, and the current results provide onlya model rather than empirical data.

Discussion

In the present study, we introduced a two-phase learning-testing experimental paradigm that uses traditional Chineselogogriphs to examine the neural basis of mental prepara-tion. During testing, subjects did not know whether the heu-ristic information attained from the learning logogriphwould be useful for solving the test logogriph. That is, sub-jects could not predict whether they would successfullysolve each test logogriph. Thus, the mental preparation forsolving test logogriphs should be similar in every trial.However, our study found that mental preparation forsuccessful logogriphs elicited a more positive ERP deXec-tion than unsuccessful logogriphs between ¡1,000 and¡800 ms before onset of the test logogriphs. Dipole analy-sis of the diVerence wave (successful logogriphs minusunsuccessful logogriphs) localized the generators of thepositive component mainly in the ACC/medial frontal areas.

During the interval time between the learning stage andthe testing stage, subjects were instructed to pay attentionto the center of the screen (“+”) and required to guess thelogogriph appeared quickly. The relationship of the baseand target logogriphs was random in each trial. DiVerencesin spatiotemporal pattern of brain activity during prepara-tion were not inXuenced by the speciWc content of the targetlogogriphs which appeared subsequently. However, themental preparation of successful logogriphs solving eliciteda more positive ERP component from ¡1,000 to ¡800 msbefore onset of the target logogriphs, compared with unsuc-cessful logogriphs solving. In the present study, the locali-zation of neuronal generators for the positive component inthe mesial ACC and the left ACC supports the view that adistinct type of mental preparation, manifested in a distinctbrain state, facilitates insight problem solving independentof speciWc problems (Kounios et al. 2006). In their study,they found mental preparation leading to insight involvesheightened activity in medial frontal areas (i.e., the ACC)associated with cognitive control and suggested that “theactivity observed in ACC prior to insight may reXectincreased readiness to monitor for competing responses,and to apply cognitive control mechanisms as needed to (a)suppress extraneous thoughts; (b) initially select prepotentsolution spaces or strategies and, if these prove ineVective,(c) subsequently shift attention to a non-prepotent solutionor strategy. Such shifts are characteristic of insight”. There-fore, Kounios et al. (2006) indicated that the increasedACC activity during the preparation period might be relatedto increased top-down control not to obvious cognitive orresponse conXict. Previous studies also indicate a correla-tion between attempted thought suppression and ACCactivity (Kiehl et al. 2000; Anderson et al. 2004). In addi-tion, some researchers argue that the ACC is involved inmonitoring the preparatory allocation of attention for con-Xict at the level of activation of competing attentional sets(Luks et al. 2002; Suchan et al. 2005), whereas othersassume that the ACC is responsible for the inhibition ofirrelevant information in working memory (George et al.1994). Moreover, Gilbert et al. (2006) made a meta-analy-ses of functional neuroimaging studies about the rostralprefrontal cortex (BA 10), and found that studies involvingworking memory and episodic memory retrieval weredisproportionately associated with lateral prefrontal cortexactivations, whereas studies involving mentalizing (i.e.,attending to one’s own emotions and mental states or thoseof other agents) were disproportionately associated withmedial prefrontal cortex (e.g., ACC) activation.

Previous studies (Luo et al. 2003, 2004; Mai et al. 2004)that catalyzed insight by presenting the correct answers alsofound that insight riddle-solving was associated with activityin the ACC and suggested that ACC activation happened inthe initial stages of insight onset, playing the role of an

Fig. 3 Results of the dipole source analysis of the diVerence wave(successful versus unsuccessful logogriphs) from ¡1,000 to ¡800 ms.The Wrst dipole is located approximately in the anterior mesial cingu-late cortex (x = 1.9, y = 6.5, z = 27.9), the second near the left anteriorcingulate cortex (x = ¡14.9, y = 25.7, z = 1.4) and the third near theright parahippocampal gyrus (x = 6.0, y = ¡8.7, z = ¡17.1)

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“early warning system” in the break of mental set. Itsknown that insight problem solving requires rethinkingsome basic assumptions about the problem content, whichhappens in a relatively sudden and unpredictable manner(e.g., Kohler 1925; Scheerer 1963). Martindale (1989) thatfound subjects could easily Wnd new associations and formcorrect representations in primary processing condition(defocused attention). That is, some form of mental prepa-ration might facilitate insight. The present results, togetherwith the previous studies, suggest that the ACC might bethe neural basis of mental preparation that could be prone tosuccessful insight problem solving.

In our study, EEGs of mental preparation were analyzedbefore onset of the target logogriphs. However, comparingto Kounios’ (2006) study, our task might be a motor prepa-ration task in which the motor response following presenta-tion of the test logogriph was cued by problem solvingduring the learning phase. Previous studies indicated thatthe ACC/medial frontal cortex were involved in mere prep-aration and execution of motor responses (Petit, Courtney,Ungerleider and Haxby 1998), action selection based on theexpected outcome of an action (Bush et al. 2002; Hadlandet al. 2003) and integrating information regarding a motorresponse and its potential outcome (Williams et al. 2004;Mars et al. 2005). Therefore, the role of ACC/medialfrontal cortex in mental and motor preparation still needsfurther investigation.

Conclusion

In the present study, the mental preparation of successfullogogriphs elicited a more positive ERP deXection thanunsuccessful logogriphs from ¡1,000 to ¡800 ms beforeonset of the target logogriphs. Dipole analysis localized thegenerators of the positive component primarily in the ACC/medial frontal areas. This result is consistent with Kounios’view that general mental preparatory mechanisms modulateproblem-solving strategy (Kounios et al. 2006).

Acknowledgements This research was supported by the NationalKey Discipline of Basic Psychology in Southwest China University(No.NSKD07002, No.NSKD06002).

References

Anderson MC, Ochsner KN, Kuhl B, Cooper J, Robertson E, GabrieliSW, Glover GH, Gabrieli JDE (2004) Neural systems underlyingthe suppression of unwanted memories. Science 303:232–235

Bowden EM, Jung-Beeman M (2003) Aha! Insight experience corre-lates with solution activation in the right hemisphere. PsychonBull Rev 10:730–737

Bowden EM, Juang-Beeman M, Fleck J, Kounios J (2005) Newapproaches to demystifying insight. Trends Cogn Sci 9:322–328

Bush G, Vogt BA, Holmes J, Jenike MA, Rosen BR (2002) Dorsalanterior cingulate cortex: a role in reward-based decision making.Proc Natl Acad Sci USA 99:523–528

Hadland KA, Rushworth MFS, GaVan D, Passingham RE (2003) Theanterior cingulate and reward-guided selection for actions.J Neurophysiol 89:1161–1164

George MS, Ketter TA, Parekh PI, Rosinsky N, Ring H, Casey BJ(1994) An H2150 PET study on the stroop and the emotionalstroop. Hum Brain Mapp 1:194–209

Gilbert SJ, Spengler S, Simons JS, Steele JD, Lawrie SM, Frith CD,Burgess PW (2006) Functional specialization within rostralprefrontal cortex (area 10): a meta-analysis. J Cogn Neurosci6:932–948

Kiehl KA, Smith AM, Hare RD, Liddle PF (2000) An event-related po-tential investigation of response inhibition in schizophrenia andpsychopathy. Biol Psychiatry 48:210–221

Kohler W (1925) The mentality of apes. Routledge and Kegan Pau,London

Kounios J, Frymiare JL, Bowden EM, Fleck JI, Subramaniam K,Parrish TB et al (2006) The prepared mind: neural activity priorto problem presentation predicts subsequent solution by suddeninsight. Psychol Sci 17:882–890

Luks TL, Simpson GV, Feiwell RJ, Miller WL (2002) Evidence foranterior cingulate cortex involvement in monitoring preparatoryattentional set. Neuroimage 17:792–802

Luo J, Niki K (2003) The function of hippocampus in ‘insight’ ofproblem solving. Hippocampus 13:274–281

Luo J, Niki K, Phillips S (2004) Neural correlates of the “Aha!Reaction”. Neuroreport 15:2013–2017

Luo Q, Perry C, Peng DL, Jin Z et al (2003) The neural substrate ofanalogical reasoning: an fMRI study. Cogn Brain Res 17:527–534

Mai XQ, Luo J, Wu JH, Luo YJ (2004) “Aha!” eVects in guessingriddle task: an ERP study. Hum Brain Mapp 22:261–270

Martindale C (1989) Personality, situation, and creativity. In: Glover J,Ronning R, Reynolds CR (eds) Handbook of creativity. Plenum,New York, pp 211–232

Mars RB, Coles MGH, Grol MJ, Holroyd CB, Nieuwenhuis S, HulstijnW, Toni I (2005) Neural dynamics of error processing in medialfrontal cortex. Neuroimage 28:1007–1013

Petit L, Courtney SM, Ungerleider LG, Haxby JV (1998) Sustainedactivity in the medial wall during working memory delays. J Neu-rosci 18:9429–9437

Qiu J, Hong L, Yuejia L, Antao C, Fenghua Z, Qinglin Z (2006) Brainmechanism of cognitive conXict in a guessing Chinese logogriphtask. Neuroreport 17:679–682

Scheerer M (1963) Problem solving. Sci Am 208:118–128Schooler JW, Fallshore M, Fiore SM (1995) Epilogue: putting insight

into perspective. In: Sternberg RJ, Davidson JE (eds) The natureof insight. MIT press, Cambridge, pp 559–588

Smith RW, Kounios J (1996) Sudden insight: all-or-none processingrevealed by speed-accuracy decomposition. J Exp Psychol LearnMem Cogn 22:1443–1462

Suchan B, Melde C, Homberg V, Seitz RJ (2005) Cingulate cortexactivation and competing responses: the role of preparedness forcompetition. Behav Brain Res 163:219–226

Weisberg RW (1995) Prolegomena to theories of insight in problem-solving: a taxonomy of problems. In: Sternberg RJ, Davidson JE(eds) The nature of insight. MIT Press, London, pp 157–196

Williams ZN, Bush G, Rauch SL, Cosgrove GR, Eskandar EN (2004)Human anterior cingulate neurons and the integration of monetaryreward with motor responses. Nat Neurosci 7:1370–1375

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