As robots increasingly integrate into human teams for critical domains, understanding the team dynamics within these multi-human-robot teams (mHRTs) becomes essential. While previous work has explored trust in human-robot interactions, there still needs to be a gap in examining how trust evolves and propagates within mHRTs. This study investigated team trust networks using neural measures in mHRTs under varying robot reliability conditions. A total of 23 teams completed search and rescue tasks in a virtual environment, with one member being an autonomous robot navigator (reliable/unreliable). Results indicate that while unreliable robot performance led to decreased trust in the robot, human dyad trust did not falter. Unreliable robot teammates weakened IBS in regions associated with individuals’ comprehension of others’ beliefs, intentions, and social judgments. These findings highlight emergent shifts in team processes under robot uncertainties that were captured using neural synchrony.