The Electrophysiological Correlates of Scientific Innovation Induced by Heuristic Information

In this study, novel and old scientific innovations (NSI and OSI) were selected as materials to explore the electrophysiological correlates of scientific innovation induced by heuristic information. Using event-related brain potentials (ERPs) to do so, college students solved NSI problems (for which they did not know the answers) and OSI problems (for which they knew the answers). A new experimental paradigm (heuristic information learning–problems testing model) was adopted to make subjects actively find a solution. The results showed that the P3 amplitude was higher for OSI than for NSI between 360 and 430 ms after onset of the problem stimuli. This finding most likely reflects an automatic matching process based on the known answer retrieval, which would be easier for OSI than NSI problems. However, the N4 amplitude was higher for NSI than for OSI between 430 and 500 ms and a greater negativity in the NSI (in comparison with OSI) developed between 500 and 900 ms. This pattern could reflect the generation of novel solutions due to the application of heuristic information (retrieved from memory) during NSI problems solving.

[1]  G. McCarthy,et al.  Augmenting mental chronometry: the P300 as a measure of stimulus evaluation time. , 1977, Science.

[2]  M. Kutas,et al.  Reading senseless sentences: brain potentials reflect semantic incongruity. , 1980, Science.

[3]  M. Kutas,et al.  The lateral distribution of event-related potentials during sentence processing , 1982, Neuropsychologia.

[4]  E. Donchin,et al.  Is the P300 component a manifestation of context updating? , 1988, Behavioral and Brain Sciences.

[5]  M. Kutas,et al.  An Electrophysiological Probe of Incidental Semantic Association , 1989, Journal of Cognitive Neuroscience.

[6]  R. Sternberg.  Handbook of Creativity: Subject Index , 1998 .

[7]  H. Berg,et al.  Cats' Paws and Catapults: Mechanical Worlds of Nature and People , 1998 .

[8]  M. Dickinson,et al.  Bionics: biological insight into mechanical design. , 1999, Proceedings of the National Academy of Sciences of the United States of America.

[9]  P. Holcomb,et al.  An electrophysiological investigation of semantic priming with pictures of real objects. , 1999, Psychophysiology.

[10]  A. Lavric,et al.  Differences in working memory involvement in analytical and creative tasks: an ERP study , 2000, Neuroreport.

[11]  C. Petten,et al.  Conceptual integration and metaphor: An event-related potential study , 2002, Memory & cognition.

[12]  X. Mai,et al.  “Aha!” effects in a guessing riddle task: An event‐related potential study , 2004, Human brain mapping.

[13]  Yue-Jia Luo,et al.  “Aha!” effects in a guessing riddle task: An ERP study , 2004 .

[14]  A Further Study of the ERP Effects of ‘Insight’ in a Riddle Guessing Task , 2005 .

[15]  A. Flaherty.  Frontotemporal and dopaminergic control of idea generation and creative drive , 2005, The Journal of comparative neurology.

[16]  Jonathan Grainger,et al.  On the Time Course of Visual Word Recognition: An Event-related Potential Investigation using Masked Repetition Priming , 2006, Journal of Cognitive Neuroscience.

[17]  Hilde Haider,et al.  Precursors of Insight in Event-related Brain Potentials , 2006, Journal of Cognitive Neuroscience.

[18]  Qinglin Zhang,et al.  The neural basis of conditional reasoning: An event-related potential study , 2007, Neuropsychologia.

[19]  Kara D. Federmeier.  Thinking ahead: the role and roots of prediction in language comprehension. , 2007, Psychophysiology.

[20]  Marta Kutas,et al.  Interplay between computational models and cognitive electrophysiology in visual word recognition , 2007, Brain Research Reviews.

[21]  Manuel Perea,et al.  Are Vowels and Consonants Processed Differently? Event-related Potential Evidence with a Delayed Letter Paradigm , 2009, Journal of Cognitive Neuroscience.

[22]  Ellen F. Lau,et al.  A cortical network for semantics: (de)constructing the N400 , 2008, Nature Reviews Neuroscience.

[23]  J. Qiu,et al.  The neural basis of insight problem solving: An event-related potential study , 2008, Brain and Cognition.

[24]  Jonathan Grainger,et al.  Watching the Word Go by: On the Time-course of Component Processes in Visual Word Recognition , 2009, Lang. Linguistics Compass.

[25]  Qinglin Zhang,et al.  The time course of Chinese riddles solving: Evidence from an ERP study , 2009, Behavioural Brain Research.

[26]  J. Qiu,et al.  The neural basis of breaking mental set: an event-related potential study , 2010, Experimental Brain Research.

[27]  A. Dietrich,et al.  A review of EEG, ERP, and neuroimaging studies of creativity and insight. , 2010, Psychological bulletin.

[28]  M. Carreiras,et al.  Electrophysiological evidence of interaction between contextual expectation and semantic integration during the processing of collocations , 2010, Biological Psychology.

[29]  Andreas Fink,et al.  Enhancing creativity by means of cognitive stimulation: Evidence from an fMRI study , 2010, NeuroImage.

[30]  J. Qiu,et al.  Neural correlates of mental preparation for successful insight problem solving , 2011, Behavioural Brain Research.

[31]  Xiao Xiao,et al.  The time course of breaking mental sets and forming novel associations in insight-like problem solving: an ERP investigation , 2011, Experimental Brain Research.