A spiking network model for clustering report in a visual working memory task - Lei, Lixing; Zhang, Mengya; Li, Tingyu; Dong, Yelin; Wang, Da-Hui (Frontiers in Computational Neuroscience, 2023)
Working memory plays a key role in many cognitive processes. Recently, it has been observed that the reports of the memorized color sampled from a uniform distribution are clustered, and the report error for the stimulus follows a Gaussian distribution. We constructed a spiking network model with heterogeneous connectivity and embedded short-term plasticity (STP). Our model can reproduce the clustering report given a stimulus sampled from a uniform distribution and the error of the report following a Gaussian distribution. Perturbation studies showed that the heterogeneity of connectivity and STP are necessary to explain experimental observations.