Revealing 'activity-silent' working memory
It is often assumed that information in working memory is maintained via persistent activity states. However recent evidence indicates that only some items in WM are associated with elevated neural activity, whereas others are effectively ‘activity-silent’. Silent WM is consistent with recent theoretical cognitive and neural models, but poses an important experimental problem: how can we study these silent states using conventional measures of brain activity?
We are exploring novel ways to probe 'activity-silent' states of working memory by selectively driving activity brain activity during maintenance in WM and measure the WM-dependent impulse response. For example, in an initial proof-of-concept, we have developed a promising and simple approach to decode ‘activity-silent’ WM content from the EEG response to a neutral visual stimulus presented in the delay period. For illustration, consider active sensing in echolocation (e.g., sonar), where a simple impulse (e.g., ‘ping’) is used to probe hidden contours of unseen structure. Analogously, the impulse response to neural perturbation should co-depend on the pattern of input activity and hidden state of the network (see schematic figure for echolocation). If the input pattern is held constant, we can attribute differences in the output to underlying changes in hidden state. Further studies will be able to exploit this general approach to study different states in working memory, implications for capacity limits and the focus of attention.
This approach could also have important implications for cognitive neuroscience in general. Indeed, the activity states that we measure using standard recording techniques are probably just the tip of the iceberg when it comes to the neural states underlying cognition. Developing new ways to infer these hidden states will open up many new opportunities.
Investigators: Mark Stokes, Michael Wolff, MaryAnn Noonan