This paper explores the development of reservoir-computing based associative memories for complex dynamical attractors, addressing two common neuropsychological scenarios: location-addressable and content-addressable retrieval. The authors demonstrate that a single reservoir computing machine can store and retrieve a large number of periodic and chaotic attractors, each identified by a specific index value. They articulate control strategies to achieve successful switching among attractors, analyze the mechanisms behind failed switching, and uncover scaling behaviors between the number of stored attractors and the reservoir network size. For content-addressable retrieval, they exploit multistability with cue signals, where stored attractors coexist in the high-dimensional phase space of the reservoir network. The success rate of retrieval increases as the length of the cue signal increases through a critical value. The work provides foundational insights into developing long-term memories and itinerancy for complex dynamical patterns. The paper also discusses the advantages of index-based and index-free memory approaches, highlighting the efficiency and scalability of the index-based method.This paper explores the development of reservoir-computing based associative memories for complex dynamical attractors, addressing two common neuropsychological scenarios: location-addressable and content-addressable retrieval. The authors demonstrate that a single reservoir computing machine can store and retrieve a large number of periodic and chaotic attractors, each identified by a specific index value. They articulate control strategies to achieve successful switching among attractors, analyze the mechanisms behind failed switching, and uncover scaling behaviors between the number of stored attractors and the reservoir network size. For content-addressable retrieval, they exploit multistability with cue signals, where stored attractors coexist in the high-dimensional phase space of the reservoir network. The success rate of retrieval increases as the length of the cue signal increases through a critical value. The work provides foundational insights into developing long-term memories and itinerancy for complex dynamical patterns. The paper also discusses the advantages of index-based and index-free memory approaches, highlighting the efficiency and scalability of the index-based method.