Different brain areas subserve performance of working memory (WM) tasks, including the basal ganglia and prefrontal cortex (PFC). A class of WM tasks, known as delayed-response tasks, has been used to assess the relevance of the basal ganglia or PFC to WM in nonhuman animals (Collins et al., 2000; Goldman-Rakic, 1995a, 1995b; Levy et al., 1997; Sawaguchi & Iba, 2001), as well as patients with basal ganglia disorders (Vermersch et al., 1999; Lewis et al., 2003). We propose a neural model that simulates performance of delayed-response tasks. An architecture, known as the Actor-Critic architecture (Houk et al., 1995), has been used to model basal ganglia-based motor and/or cognitive functions (Berns & Sejnowski, 1996; Suri & Schultz, 1998, 1999; Suri et al., 2001). We incorporate this architecture to model performance in delayed-response tasks. The model is trained using a reward-based learning algorithm known as the temporal difference algorithm. The model assumes that PFC subserves maintenance of information in WM, while the basal ganglia subserve selection of motor- and cognitive-related information (Prescott et al., 2003; Redgrave et al., 1999). In this talk, I will discuss experimental and modeling studies (including the proposed model) related to performing delayed-response tasks.