A dynamical network can be viewed as a set of dynamical systems that influence each other. Dynamical networks with identical systems are a special case of such networks. Making all the systems in such a network behave in the same manner termed as "synchronizing the network to a system trajectory" is a well studied topic.
We investigate the synchronization in networks where the system influences vary over time, leveraging concepts from the Temporal Network framework. Our focus lies in determining if synchronization can propagate across the entire network by initially synchronizing (pinning) only a subset of systems, relying solely on system interactions. We establish sufficient conditions for this scenario and formulate an optimization problem to minimize the number of initial pinning nodes required for network synchronization. Moreover, we tackle the problem of maximizing synchronized nodes under constraints on the number of nodes that can be pinned, demonstrating its NP-hard nature and proposing a greedy heuristic. Numerical simulations validate our findings.