Landmarks: A solution for spatial navigation and memory experiments in virtual reality.

Research into the behavioral and neural correlates of spatial cognition and navigation has benefited greatly from recent advances in virtual reality (VR) technology. Devices such as head-mounted displays (HMDs) and omnidirectional treadmills provide research participants with access to a more complete range of body-based cues, which facilitate the naturalistic study of learning and memory in three-dimensional (3D) spaces. One limitation to using these technologies for research applications is that they almost ubiquitously require integration with video game development platforms, also known as game engines. While powerful, game engines do not provide an intrinsic framework for experimental design and require at least a working proficiency with the software and any associated programming languages or integrated development environments (IDEs). Here, we present a new asset package, called Landmarks, for designing and building 3D navigation experiments in the Unity game engine. Landmarks combines the ease of building drag-and-drop experiments using no code, with the flexibility of allowing users to modify existing aspects, create new content, and even contribute their work to the open-source repository via GitHub, if they so choose. Landmarks is actively maintained and is supplemented by a wiki with resources for users including links, tutorials, videos, and more. We compare several alternatives to Landmarks for building navigation experiments and 3D experiments more generally, provide an overview of the package and its structure in the context of the Unity game engine, and discuss benefits relating to the ongoing and future development of Landmarks.

Roles of human hippocampal subfields in retrieval of spatial and temporal context.

While numerous studies indicate the involvement of the hippocampus in encoding and retrieval of spatial and temporal context, the neural basis of spatial and temporal processing within the hippocampal circuit remains unclear. We employed a novel paradigm in which participants encoded stores within a spatial layout by visiting them in a specific temporal order. Participants then underwent high-resolution functional magnetic resonance imaging (fMRI) targeting the hippocampus while retrieving details of the spatial or temporal context in alternating blocks. During retrieval, participants made judgments about either near or far intervals within the spatial layout or temporal sequence. Across both near and far intervals, we found that retrieving spatial layout and temporal order information resulted in comparable levels of activation in the hippocampus that was not preferentially localized to a specific subfield. Furthermore, using a multivariate approach called multivariate pattern similarity analysis (MPSA), we found that correct near judgments vs. correct far judgments differed in their patterns of activity for spatial vs. temporal order judgments. Despite these differences in MPSA patterns, we did not find any specific subfields differentially recruited for spatial vs. temporal order retrieval. We discuss our results in terms of their relation to computational models of hippocampal subfield function and suggest mechanisms by which the hippocampus could process space and temporal order without the need for specific contributions from hippocampal subfields.