Abstract Two studies used word puzzles that required participants to find a word that satisfied a set of constraints. The first study used a remote associates task, where participants had to find a word that would form compound words with three other words. The second study required participants to complete a word fragment with an associate of another word. Both studies produced distinct patterns of activity in the ventrolateral prefrontal cortex (VLPFC) and the anterior cingulate cortex (ACC). Activation in the VLPFC rose only as long as the participants were trying to retrieve the solution and dropped off as soon as the solution was obtained. However, activation in the ACC increased upon the retrieval of a solution reflecting the need to process that solution. An ACT-R model was fit to the data of the second experiment. The ACT-R theory interprets the activity in the VLPFC as reflecting retrieval operations and the activity in the ACC as the setting of control states or subgoals. The data confirm these interpretations over alternative interpretations.
Studies of cognitive neuroimaging have consistently shown that medial and lateral areas of the prefrontal cortex are active when participants are engaged in cognitively demanding tasks (e.g., Botvinick et al., 2001; Bunge & Wallis, 2007; Fincham & Anderson, 2006; MacDonald et al., 2000; Schneider & Cole, 2007). However, the field is still trying to articulate the precise roles of different prefrontal regions. The current work uses event-related functional magnetic resonance imaging (fMRI) to investigate two particular components of cognitive demand: the need to retrieve specific information and the need to control the direction of cognition. The studies reported will test whether a region in the ventrolateral prefrontal cortex (VLPFC) reflects memory retrieval demand and a region in dorsal anterior cingulate cortex (ACC) reflects goal-relevant control demand. The studies use special properties of word puzzle tasks to separate the functions of these two regions.
Our understanding of these regions is informed by the ACT-R cognitive architecture (Anderson et al., 2004; Anderson, 2007) that is capable of making explicit the computations underlying task performance. According to the ACT-R theory, cognition emerges through the interaction of a number of relatively independent modules. Figure 1 identifies these modules and their brain associations. Later the paper will describe an ACT-R model that involves 6 of these modules, but the principal focus is on the VLPFC region and the ACC region (regions 6 and 7 in Figure 1).
Theories of the Ventrolateral Prefrontal Cortex and the Anterior Cingulate Cortex
The human prefrontal cortex is a large structure and consists of many distinct areas, both in terms of structure and function (e.g., Miller & Cohen, 2001; Petrides, 2005). The ventrolateral region has been associated with retrieval factors in imaging studies (e.g., Buckner, 1999; Cabeza et al., 2002; Fletcher & Henson, 2001; Wagner, 2001). It is also active in many tasks particularly those involving language. Badre and Wagner (2007) suggest that the involvement of this region in such tasks can be understood in terms of retrieving the information needed to perform the tasks.
We hypothesize that this region serves the role of maintaining the retrieval cues for accessing information stored elsewhere in the brain. The longer it takes to complete the retrieval successfully, the longer the cues will have to be maintained and the greater the activation. Focused studies that manipulate retrieval difficulty produce systematic differences in the activation of this region. This region (and not other regions in Figure 1) tends to respond to manipulations of fan or associative interference (Sohn et al., 2003, 2005), retention delay (Anderson et al., 2008), and repetition (Danker et al., in press). These are all factors that influence the duration of a single retrieval from declarative memory. Perhaps the major competing interpretation of this prefrontal region is that it is activated in conditions that require difficult selections among retrieved information (e.g., Moss et al., 2005; Thompson-Schill et al., 1997). On the other hand, it has been argued that these effects are due to greater retrieval demands in the more difficult conditions (Martin & Cheng, 2005; Wagner et al., 2001). The research reported here will be relevant to adjudicating this difference.
The ACC region is associated with ACT-R’s goal module that is responsible for setting subgoals or control states that enable different courses of information processing to be taken when participants are in otherwise identical problem states. It thus enables internal control of cognition independent of external circumstances. The subgoals determine which branch is taken at decision points in the information processing. This sense of “control” is basically the same as in computer science where it indicates how the state transitions within a system are shaped and it is similar to some theories of the ACC (e.g., Desposito et al., 1995; Posner & Dehaene, 1994; Posner & DiGirolamo, 1998;). However, other theories relate ACC activity to error detection, (e.g., Falkenstein et al., 1995; Gehring et al.), response conflict (Botvinick et al., 2001; Carter et al., 2000; Yeung et al., 2004), or the likelihood of an error (Brown & Braver, 2005). Again the research to be reported here will be relevant to distinguishing among these various possibilities.
Exposing the Cycle of Central Cognition using Word Puzzle Problems Cognitively demanding tasks tend to involve a cycle of retrieval and state changes. The system will be in some state (for instance, in the midst of solving an equation like 2x – 3 = 5) and make a request for retrieval of a declarative fact (such as what is the sum of 5 plus 3?). With the retrieval of this information the system may need to change its internal state (e.g., change the mental representation of the equation to 2x = 8 and set a subgoal to perform division). This then in turn can evoke another retrieval request (e.g., what is 8 divided by 2?). Thus, the cycle is one in which the current state of internal representations evoke requests for declarative retrievals and the system may change its state to reflect the retrieved information. The mappings in Figure 1 imply that the retrieval operations will be reflected in the activity of the VLPFC, the changes to the problem representation in the activity of the posterior parietal region, and the subgoal changes in the activity of the ACC. Many researchers have noticed that these regions tend to activate together and this is what ACT-R would expect given this information-processing cycle (e.g., Cabeza et al., 2003; Dorsenbach et al., 2006; Schneider & Cole, 2007).
The research to be reported here will capitalize on a feature of certain word puzzles that allow us to pull apart the retrieval module from the goal module. The first experiment will use remote association problems introduced by Mednick (1962). Participants saw three words (e.g., pine, crab, and sauce) and attempted to produce a single solution word (i.e., apple) that can form compound words with each of the hint words (i.e., pineapple, crabapple, and applesauce). In the ACT-R model for this task a goal is set to find a solution and the retrieval module is continuously engaged until the problem is solved. The important characteristic about these problems is that it takes a long time to retrieve a solution if one is retrieved at all. This produces a sustained demand on the retrieval module while the goal module is dormant in a fixed state. In terms of predictions for the BOLD response this implies that activity should be increasing in the VLPFC (retrieval module) while it is dropping off in the ACC (goal module). However, once the problem is solved, activity will stop in the retrieval module while activity will re-emerge in the goal module to set the subgoals to process the solution. Then the patterns of BOLD activity should reverse and activity should increase in ACC while it decreases in VLPFC. This is the same cycle as in many tasks but because the retrieval phase can be so long it should be possible in this task to see the separation of the stages despite the limited temporal resolution of fMRI.
In imaging research Jung-Beeman et al. (2004) and Kounios et al. (in press) used the remote compound solutions from Bowden and Jung-Beeman (2003), adapted from the work of Mednick (1962). Their main research interest was in the contrast between solutions that were solved with a reported experience of insight and those that were not. In contrast the current experiment will simply contrast solutions with non-solutions. If they could find imaging effects reflecting the rather subtle difference between problems solved with a feeling of insight and problems solved without, this experiment should be able to detect differences based on the contrast between solution trials and non-solution trials and so it follows their procedures fairly closely.
Twenty right-handed members of the Pittsburgh community (11 females) aged 18 to 32 years old (mean = 23.2 years) completed the study.
Participants were presented with 3 hint words that could be combined with a common word and participants had to produce this common word. For example, the words print, berry, and bird can all be combined with blue (i.e., blueprint, blueberry, bluebird). In this study, as in the Jung-Beeman et al. study, the participants were presented with the three hint words for up to 30 s. If at any time they were able to identify the word, they pressed a button on a data-glove and were taken to a solution screen. They were then given 5 s in which to speak the target word. After this they were presented with a screen that asked if they had solved the problem with insight and they had up to 5 s to respond. The insight screen instructed them to respond ‘yes’ by pressing their index finger button and ‘no’ by pressing their middle finger button. During instruction, the participants were given the following definition of insight (taken from Jung-Beeman et al., 2004):
A feeling of insight is a kind of 'Aha!' characterized by suddenness and obviousness. You may not be sure how you came up with the answer, but are relatively confident that it is correct without having to mentally check it. It is as though the answer came into mind all at once - when you first thought of the word, you simply knew it was the answer. This feeling does not have to be overwhelming, but should resemble what was just described (p.507).
After making their insight response, they were presented with a fixation for 9.5 to 11.5 s (to the start of a new 2 s scan of a volume) and then a new trial began.
If unable to solve the problem in the 30 s, the participant was then taken to a screen that presented the target word as well as the three hint words. This screen lasted for 5 s, and was followed by an 11 s fixation before the next set of hint words was presented.
Participants were given instruction and 20 practice trials during structural scans. The instruction included one example of three cue words and a solution word. Participants were asked to solve 63 problems during one scan session, which were broken into blocks of 9 to 10 min. These 83 problem/solution combinations were randomly selected from a pool of 144 found in Bowden & Jung-Beeman (2003).
Images were acquired using gradient echo-echo planar image (EPI) acquisition on a Siemens 3T Allegra Scanner using a standard RF head coil (quadrature birdcage), with 2 s repetition time (TR), 30ms echo time (TE), 70 flip angle, and 20cm field of view (FOV). The experiment acquired 34 axial slices on each TR using a 3.2mm-thick, 64×64 matrix. The anterior commissure-posterior commissure (AC-PC) line was on the 11th slice from the bottom scan slice.
Acquired images were analyzed using the NIS system. Functional images were motion-corrected using 6-parameter 3D registration (AIR, Woods et al., 1998). All images were then co-registered to a common reference structural MRI by means of a 12-parameter 3D registration (AIR, Woods et al.) and smoothed with an 8 mm full-width-half-maximum 3D Gaussian filter to accommodate individual differences in anatomy. Spatial F maps were generated using random effects analysis of variance (ANOVA).