The Cognitive Control & Aging Lab conducts research in four primary areas:

  1. 1) Mechanisms of cognitive control

    A current focus of our studies is investigating stimulus-driven or reactive cognitive control mechanisms that resolve interference in conflict tasks such as Stroop and flanker. These mechanisms involve rapid adjustments of attention which are triggered by the processing of stimuli or stimulus features, and appear to be implicit in nature. As such, they contrast strongly with the strategic, deliberate, and slow -acting cognitive control mechanisms classically described as top-down or more recently, proactive control.  Our research examines two stimulus-driven mechanisms, item-specific control and context-specific control. One aim of our studies is teasing apart the contribution of these mechanisms from the contribution of other “non-control” mechanisms such as associative learning, which can masquerade as cognitive control in tasks such as Stroop (e.g., Bugg, Jacoby, & Chanani, 2011). A second aim is to identify those contextual and individual differences factors that modulate participants’ reliance on stimulus-driven cognitive control and associative learning  (e.g., Bugg & Hutchison, 2013).

    Another focus of our research is dissociating stimulus-driven control from top-down control. Our prior research has called into question whether the list-wide proportion congruence effect (i.e., greater interference in mostly congruent as compared to mostly incongruent lists), a pattern classically attributed to global, top-down control strategies, might be accounted for by stimulus-driven cognitive control mechanisms (Bugg, Jacoby, & Toth, 2008). We have demonstrated a set of conditions under which one can demonstrate use of top-down cognitive control, independent of stimulus-driven mechanisms, in list-wide proportion congruence paradigms (Bugg & Chanani, 2011; Bugg, McDaniel, Scullin, & Braver, 2011). Most recently, we have shown that engagement of top-down control in the face of a high degree of conflict (i.e., mostly incongruent lists) varies depending on the degree to which task goals can be achieved via associative S-R learning (Bugg, 2014). In general, our lab is interested in how and when participants engage preparatory strategies for minimizing interference.

  1. 2) Age-related declines in, as well as preservation of, cognitive control mechanisms

    Our basic research on cognitive control mechanisms stimulates the question of whether aging has a differential effect on stimulus-driven and top-down cognitive control. Our initial findings suggests age-related changes in top-down control (Bugg, 2014), whereas changes in stimulus-driven interference control are weaker or absent (Bugg, 2014). We are currently collecting data to rule out alternative accounts of these findings and extend the work to other domains of cognitive control.

  1. 3) Cognitive control and prospective remembering and forgetting in young and older adults

    Prospective remembering refers to the ability to remember to perform an action at the appropriate time in the future. Examples include remembering to take a medication daily at 6:00 pm and remembering to pick up milk when you drive by the grocery store on the way home from work.  Of theoretical and practical significance is not only the ability to remember to perform intended actions, but also the ability to forget or “deactivate” completed intentions.  Imagine the mental clutter that would exist if you were unable to forget previously relevant intentions (e.g., those you performed 10 min ago, 3 hours ago, or even days ago). Our research shows that older adults are more susceptible than young adults to commission errors, erroneously repeating a completed (and therefore, no-longer relevant) prospective memory action, particularly when cues (external or internal) are present that remind participants of the previously relevant intention (Scullin, Bugg, & McDaniel, 2011). We have also found that risk of commission errors increases when younger adults are fatigued (Scullin & Bugg, 2013), and when the intention is strongly encoded  (Bugg, Scullin, & McDaniel, 2013).

    A third area of focus concerns the role of conflict in prospective remembering. We have found that in contexts where conflict is frequent (relative to infrequent), participants are more likely to filter out stimulus features that tend to produce conflict in a global fashion, such that they fail to detect and respond to prospective memory target cues that are embedded in such features (Bugg, McDaniel et al., 2011). A real world analogy is that of driving in rush-hour traffic while looking for a particular cafe’. Globally filtering the variety of distracting stimuli along your route in order to focus on driving effectively and safely may lead you to filter out that cafe’ you are looking for. Experiencing conflicts in information processing may not always have a negative impact on prospective remembering, however. In an ongoing study in collaboration with a graduate student, Jihae Lee, the lab is examining the idea that processing conflicts may benefit prospective remembering. In particular, this study focuses on the potentially facilitative effects of discrepancy signals (that result from an information processing conflict) on prospective remembering in an implicit learning task.

  1. 4) Factors moderating cognitive control performance for older adults including exercise and cognitive training

    Prior research, including studies from our lab (e.g., Bugg & Head, 2011), has examined the relationship between engagement in physical activity or exercise and cognitive function/brain health. There has also been much interest in the literature in the potential benefits of cognitive training for older adults’ cognitive function. My colleagues Ellen Binder and Mark McDaniel and I, and our research team, completeda 3-year NIA funded study examining the independent and combined effects of Exercise and Cognitive Training on older adults’ cognitive function, as assessed by traditional neuropsychological tests and real-world like laboratory tasks. We found select benefits of cognitive training for performance on prospective memory tasks (McDaniel et al., in press).

Research Interests

The Cognitive Control & Aging Lab is in the Department of Psychology at Washington University in St. Louis.

Contact Info:

Campus Box 1125

1 Brookings Dr.          

St. Louis, MO 63130

Ph: 314.935.4434

Figure 2. A control-driven  item-specific proportion congruence effect  that cannot be accounted for by associative learning (Bugg, Jacoby, & Chanani, 2011).

Figure 1. Classic approach to manipulating item-specific proportion congruence (upper panel) and item-specific proportion congruence effect that results (Jacoby, Lindsay, & Hessels, 2003). Highlighted cells are those for which associative learning could be speeding responses.

Figure 3. Age-related increase in commission errors.

Figure 4. Selectively slowed responding for participants in the long-delay condition who made a commission error, a pattern suggestive of fatigue.