Chang Yan: Neural Representation of Working Memory Contents At Different Levels of Abstraction

BCCN Berlin / GRK 1589 / Humboldt-Universität zu Berlin

Abstract

Working memory refers to the temporary maintenance of information and the manipulation of memorized contents. Research on the neural basis of working memory has received broad attention in recent years but has mainly focused on storage of sensory content. Evidence on short-term maintenance of abstract verbal or categorical information is scarce. This thesis aims to investigate neural representation of working memory content at different levels of abstraction. I present here three empirical studies that employed fMRI, multivariate pattern analysis or probabilistic model as major methods. The first study identified cortical regions that retained working memory content of a script. Native Chinese speakers were asked to memorize well-known Chinese characters which strongly facilitated verbal coding. Results indicated left lateralized language-related brain areas as candidate stores for verbal content. The second and the third studies aimed to test the hypothesis that color is memorized as a combination of the low-level visual representation and the abstract categorical representation. The second study utilized a conventional sensory encoding model and a novel empirical-based categorical encoding model to characterize two sources of neural representations. Color information was decoded in all three color-related ROIs: V1, V4 and VO1. Notably, an elevation in categorical representation was observed in more anterior cortices, indicating a gradient of abstraction levels in memory content along the rostral-caudal axis of the brain. In the third study, the delayed behavioral response was examined, which exhibited a systematic bias pattern; a probabilistic dual-content model was implemented, which produced response patterns highly correlated with experimental results; this confirmed the hypothesis of dual-content mnemonic representations. These studies together suggest a division of labor between cortices based on the abstraction level of memorized contents.

 

Additional Information

PhD defense in the research training group GRK 1589, 'Sensory Computation in Neural Systems'.

Organized by

Prof. Dr. John-Dylan Haynes & Dr. Thomas Christophel