Theories of cognition inform our decisions when designing human-computer interfaces, and immersive systems enable us to examine these theories. This work explores the sensemaking process in an immersive environment through studying both internal and external user behaviors with a classical visualization problem: a visual comparison and clustering task. We developed an immersive system to perform a user study, collecting user behavior data from different channels: AR HMD for capturing external user interactions, functional near-infrared spectroscopy (fNIRS) for capturing internal neural sequences, and video for references. To examine sensemaking, we assessed how the layout of the interface (planar 2D vs. cylindrical 3D layout) and the challenge level of the task (low vs. high cognitive load) influenced the users' interactions, how these interactions changed over time, and how they influenced task performance. We also developed a visualization system to explore joint patterns among all the data channels. We found that increased interactions and cerebral hemodynamic responses were associated with more accurate performance, especially on cognitively demanding trials. The layout types did not reliably influence interactions or task performance. We discuss how these findings inform the design and evaluation of immersive systems, predict user performance and interaction, and offer theoretical insights about sensemaking from the perspective of embodied and distributed cognition.