Dimensional Complexity of the EEG During Divergent and Convergent Thought Processes
Creativity is one of the most difficult mental functions to study. While a concrete definition remains illusive, it has been established as a multifaceted phenomenon (Kitto, Lok & Rudowicz, 1994). One facet that is an important component of creative potential is divergent thinking (Vosburg, 1998), this is the ability to generate several alternative solutions to a problem. The mental processing involved occurs in such a way as to activate as many mental representations as possible, maintaining only a weak connection to the original stimulus (Molle, Marshall, Wolf, Fehm & Born, 1999). One of the more popular methods for assessing creative potential then, is through the administration of divergent thinking tests (Mumford, Marks, Connelly , Zaccaro & Johnson, 1998). In these tests people are requested to generate as many alternative answers as possible to a series of ill-defined, open-ended problems (Brown, 1989). The number of ideas used in answering the problem are counted, and can be taken as a performance measure of creative thinking.
On the other side of the scale is convergent thinking. Here, very strong mental associations are maintained which upon activation come to a single conclusion that can only be either right or wrong , with a clear connection between the mental representation and the original stimulus (Molle et al., 1999). Thus, two opposite modes of thinking seem to exist, each serving a different function and each having tests that tap into this function.
What is of interest, however is the fact that little physical evidence has been collected to support these models. Finding an actual physical correlate for these theories is the purpose if this exploratory research. If creativity exists, then it should have some biological foundation. One way to study this is with the use of the electroencephalogram (EEG). The dimensional complexity of the EEG can be used to establish a differentiation of divergent and convergent thought. This can occur because the measure of dimensional complexity of the EEG activity is sensitive enough to discriminate cortical processing invoked by tasks of divergent creative thinking as compared with tasks requiring convergent analytical thought (Molle at al., 1999).
According to Hebb, as stated in Molle et al. (1999), an assembly of cells represents the functional processing unit of the brain. These assemblies represent closed systems with freer flow of information within a system, as opposed to between systems (Molle et al. 1999). It follows from this that two or more units can be active at the same time, while maintaining autonomy. The number of cell assemblies activated can be taken as an indicator of how complex the neuronal computations of the brain are at that precise moment (Molle et al. 1999). This complexity is manifested in the EEG activity. It can be assumed that the dimensional complexity of the EEG indicates the complexity of neural dynamics underlying the EEG time series. Studies by Lutzenberger, Preissl, and Pulvermuller (1995) as stated by Molle et al. (1999), suggests that a task of divergent thinking requires a larger number of cell assemblies compared to a task of convergent thinking, where only one right answer has to be found. This difference should be illustrated through the EEG’s dimensional complexity.
The study to be undertaken will look at the EEG dimensional complexity of subjects as they perform both divergent thought tasks and convergent thought tasks. Of interest is whether a substantial difference in recordings will be apparent. Does divergent thinking require more complex cortical processing? Is so, in what area of the brain is this taking place.? These are the two main questions at the heart of this study.
As the aim of this study is to look at normal brain function, volunteers will be selected from a first year psychology class. Fifteen males and fifteen females will be chosen.
The experiment will occur in an electrically shielded room. Participants will sit in a reclining chair, while the experimenter sits beside them just outside their visual field. They will be given four verbal tasks. Two of the tasks will require divergent thinking, and two will require convergent thinking. The divergent tasks will resemble those administered by Molle et al (1999). Logic and arithmetic skills will have to be employed for the convergent tasks. These tasks will consist of textbook type problem solving questions, where only one right answer exists. In this experiment, these tasks are the independent variable.
The EEG, which is the dependent variable of interest, will be monitored from a separate room. The recording sites on the subjects would be on the frontal, central, parietal and occipital cortical regions. Half the subjects will do the convergent task first, and the other half would do the divergent task first. They will be given 30s to complete each task. Between task switches, each subject will be asked to relax and think of being in some pleasing environment. EEG recordings during this time will be used as an extra comparison to those seen during the tasks. Subjects will also be asked to fixate on a point on the opposite wall. This request will help to rule out mental activity that results from visual stimuli. If tasks using divergent and convergent thought invoke different cortical processes, this distinction should be made apparent by the EEG’s dimensional complexity. The different frequencies of brain waves will have varying levels of activity.
Divergent thinking performance will be scored according to a pre-established order. Namely, points will be awarded for the number of responses given. The convergent task will either be right or wrong. The scoring is being kept simple because the experiment is of an exploratory nature. The primary purpose being to seek out any sort of relationship between brain activity and creative thought processes.
Like the study conducted by Molle et al. (1999), it is expected that divergent thinking will likely increase the dimensional complexity of the EEG in comparison to convergent thinking. Areas where there was a significant difference included the frontal, parietal and occipital regions (Molle et al., 1999). It is also expected that divergent thinking will have higher cortical activity in the central, parietal and occipital regions in comparison to mental relaxation (Molle et al. 1999).
A feel for the nature of the biology of creative thinking is lacking so far, and is the primary reason for this study. Preliminary research of this nature is needed before any specific studies can be seriously undertaken. Research into the physiological footing of creative thought has the potential to be of great aid to the field of creative psychology, lending much needed validity to many of the ideas being theorized.
Brown, R.T. (1989). Creativity. What are we to measure? In J.A. Glover, R.R. Ronning, & C.R. Reynolds (Eds.). Handbook of creativity (pp.3-32). New York: Plenum.
Kitto, J., Lok, D., & Rudowicz, E. (1994). Measuring creative thinking: an activity-based approach. Creativity Research Journal,7, 59-69.
Molle,M., Marshall, L., Wolf, B., Horst, L., & Born, J. (1999). EEG complexity and performance measures of creative thinking. Psychophysiology, 36, 95-104.
Mumford, M.D., Marks, M.A., Connelly, M.S., Zaccaro, S.J., & Johnson, J.F. (1998). Domain-based scoring of divergent-thinking tests: validation evidence in an occupational sample. Creativity Research Journal, 11, 151-163.
Vosburg, S.K., (1998). The effects of positive and negative mood on divergent-thinking performance. Creativity Research Journal, 11, 165-172.
Brown, R.T. (1989). Creativity. What are we to measure? In J.A. Glover, R.R. Ronning, & C.R. Reynolds (Eds.). Handbook of creativity (pp.3-32). New York: Plenum.
Kitto, J., Lok, D., & Rudowicz, E. (1994). Measuring creative thinking: an activity-based approach. Creativity Research Journal,7, 59-69.
Molle,M., Marshall, L., Wolf, B., Horst, L., & Born, J. (1999). EEG complexity and performance measures of creative thinking. Psychophysiology, 36, 95-104.
Mumford, M.D., Marks, M.A., Connelly, M.S., Zaccaro, S.J., & Johnson, J.F. (1998). Domain-based scoring of divergent-thinking tests: validation evidence in an occupational sample. Creativity Research Journal, 11, 151-163.
Vosburg, S.K., (1998). The effects of positive and negative mood on divergent-thinking performance. Creativity Research Journal, 11, 165-172.
