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Working memory (WM) is a capacity- and duration-limited system that forms a temporal bridge between fleeting sensory phenomena and possible actions. But how are the contents of WM used to guide behavior? A recent high-profile study reported evidence for simultaneous access to WM content and linked motor plans during WM-guided behavior, challenging serial models where task-relevant WM content is first selected and then mapped on to a task-relevant motor response. However, the task used in that study was not optimized to distinguish the selection of spatial versus nonspatial visual information stored in memory, nor to distinguish whether or how the chronometry of selecting nonspatial visual information stored in memory might differ from the selection of linked motor plans. Here, we revisited the chronometry of spatial, feature, and motor selection during WM-guided behavior using a task optimized to disentangle these processes. Concurrent EEG and eye position recordings revealed clear evidence for temporally dissociable spatial, feature, and motor selection during this task. Thus, our data reveal the existence of multiple WM selection mechanisms that belie conceptualizations of WM-guided behavior based on purely serial or parallel visuomotor processing.

 

Although inattention is a key symptom subdomain of attention-deficit/hyperactivity disorder (ADHD), the mechanisms underlying this subdomain and related symptoms remain unclear. There is a need for more granular approaches that allow for greater specificity in linking disruptions in specific domains of cognitive performance (e.g., executive function and reward processing) with behavioral manifestations of ADHD. Such approaches may inform the development of more targeted therapeutic interventions. Here, we describe the results of a pilot study of elementary-aged children (ages 6–12years) with ADHD ( n =50) and typically developing children ( n =48) utilizing a cognitive science task designed to target two dissociable mechanisms of attentional selection: a goal-driven mechanism (i.e., reward/value-driven) and a salience-driven mechanism. Participants were asked to optimally extract and combine information about stimulus salience and value to maximize rewards. While results of this pilot study are ambiguous due to the small sample size and limited number of task trials, data suggest that neither participants with ADHD nor typically developing participants performed optimally to maximize rewards, though typically developing participants were somewhat more successful at the task (i.e., more likely to report high-value targets) regardless of task condition. Further, the manuscript examines several follow-up questions regarding group differences in task response times and group differences in task performance as related to sustained attention across the duration of the task. Finally, the manuscript examines follow-up questions related to heterogeneity in the ADHD group (i.e., age, DSM 5 presentation, and comorbid diagnosis) in predicting task performance.