Atsushi Kikumoto

The Nature of Task Set Representations in Working Memory

Selection and preparation of action plans (task sets) is often assumed to occur in working memory (WM). Yet, the absence of consistent evidence that WM capacity and task selection efficiency is correlated raises questions about the functional relationship between these two aspects of executive control. We used the EEG-derived contralateral delay activity (CDA) to index the WM load of task sets. In Experiment 1, we found a CDA set size effect (2 vs. 4 stimulus–response [S-R] rules) for high-WM, but not for low-WM, individuals when S-R sets were novel. In contrast, when only four task sets were presented throughout the experiment, we observed a sustained yet set size-independent use of WM for high-WM participants. Moreover, Experiment 2 showed an increase of the CDA in situations with task conflict, and this effect was larger the more that participants experienced RT conflict effects. Combined, these results indicate that even highly familiar S-R settings are maintained in WM, albeit in a compressed manner, presumably through cues to long-term memory representations. Finally, participants with low-WM capacity represented even familiar tasks in a load-dependent manner, suggesting that the establishment of effective retrieval structures itself is a capacity-limited process.

Decoding Hierarchical Control of Sequential Behavior in Oscillatory EEG Activity

Despite strong theoretical reasons for assuming that abstract representations organize complex action sequences in terms of subplans (chunks) and sequential positions, we lack methods to directly track such content-independent, hierarchical representations in humans. We applied time-resolved, multivariate decoding analysis to the pattern of rhythmic EEG activity that was registered while participants planned and executed individual elements from pre-learned, structured sequences. Across three experiments, the theta and alpha-band activity independently coded basic elements and abstract control representations, in particular the ordinal position of basic elements, but also the identity and position of chunks. Further, a robust representation of higher-level, chunk identity information was only found in individuals with above-median working memory capacity, potentially providing a neural-level explanation for working-memory differences in sequential performance. Our results suggest that by decoding oscillations we can track how the cognitive system traverses through the states of a hierarchical control structure.

EEG Decoding Reveals the Temporal Dynamics and Functional Relevance of Goal-Relevant Representations in Humans

Models of action control assume that abstract task-set settings regulate lower-level stimulus/response representations. Yet, we know little about the functional and dynamic properties of task-set representations in humans. Using a cued task-switching paradigm, we show that information about task sets and lower-level stimulus/response aspects can be extracted through decoding analyses from the scalp electrophysiological signal (EEG) on the single-trial level and with high temporal resolution. Task-sets are active throughout the entire processing cascade and trial-to-trial variations in task-set strength emerges as a remarkably strong predictor of variability in performance, both within and between individuals. Also, taskset strength is related to stimulus representation strength at an early period and to the strength of response representations at a later period, consistent with the notion that task-sets coordinate successive, lower-level representations in a concurrent manner. These results demonstrate a powerful approach towards uncovering stages of information processing and their relative importance for performance.