picture of Savannah Chavez presenting his/her poster: STREAM OF CONSCIOUSNESS AND THE DEFAULT NETWORK

Savannah Chavez , Mary-Frances O'Connor, Matthias Mehl, John Allen


There is growing evidence that what people are thinking in an un-focused, “default” state is an important index of their psychological adjustment. In this study, we sought to identify predictors of depression from participants’ spontaneous, undirected thoughts, also known as “default mode network” activity. Prior research has shown that depression is associated with increased self-awareness and a more frequent use of the first-person singular. Specifically, we were interested in how variability in this spontaneous self-referencing maps onto depressive symptoms. To accomplish this, 61 participants completed a 20-minute stream-of-consciousness writing task where they recorded their thoughts as they naturally occurred (uncensored and unedited for grammar, spelling, etc.). The stream-of-consciousness task was preceded or followed by a survey battery (a counterbalanced design), including the Beck Depression Inventory and other personality measures. A subsample of ten participants additionally performed a stream-of-consciousness thinking (or, “default network”) task in an MRI scanner, where they were allowed to think freely for the same period of time as the written task. This portion of the study served to gauge the activation in regions of the brain associated with stream-of-consciousness thinking. The participants’ essays were then analyzed using a word count-based text analysis program that identifies the relative frequency of grammatical (e.g. personal pronouns) and psychological variables (e.g. emotion words). Information on participants’ word use during the stream-of-consciousness task is positively correlated with depression scores (r = .25, p < .03). In the MRI scans we expect to see activation in the regions denoted by the default network, and correlations between the degree of activation, depression scores, and higher pronoun use.


Funding for this project was provided by the Undergraduate Biology Research Program at the University of Arizona.

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