Distributed Patterns of Activity in Sensory Cortex Reflect the Precision of Multiple Items Maintained in Visual Short-Term Memory

TLDR

Visual short‑term memory has traditionally been linked to load‑sensitive sustained activity, yet recent work shows a single item can be decoded from early visual cortex without such sustained signals. This study tests whether sensory‑cortex activity patterns vary with memory load, as would be expected if the region stores multiple representations. Multivoxel pattern analysis was applied to human fMRI data to probe VSTM representations across varying loads. The results reveal that VSTM content is decodable from transiently responsive visual areas but not from sustained‑activity regions, with decoding accuracy dropping with load and tracking mnemonic precision, demonstrating that distributed sensory‑cortex patterns encode both representation and precision.

Abstract

Traditionally, load sensitivity of sustained, elevated activity has been taken as an index of storage for a limited number of items in visual short-term memory (VSTM). Recently, studies have demonstrated that the contents of a single item held in VSTM can be decoded from early visual cortex, despite the fact that these areas do not exhibit elevated, sustained activity. It is unknown, however, whether the patterns of neural activity decoded from sensory cortex change as a function of load, as one would expect from a region storing multiple representations. Here, we use multivoxel pattern analysis to examine the neural representations of VSTM in humans across multiple memory loads. In an important extension of previous findings, our results demonstrate that the contents of VSTM can be decoded from areas that exhibit a transient response to visual stimuli, but not from regions that exhibit elevated, sustained load-sensitive delay-period activity. Moreover, the neural information present in these transiently activated areas decreases significantly with increasing load, indicating load sensitivity of the patterns of activity that support VSTM maintenance. Importantly, the decrease in classification performance as a function of load is correlated with within-subject changes in mnemonic resolution. These findings indicate that distributed patterns of neural activity in putatively sensory visual cortex support the representation and precision of information in VSTM.