UC Irvine

It is often assumed that travel direction is redundant with head direction, but from first principles it is clear that these two factors provide differing spatial information regarding one’s orientation in the environment. Although head direction has been found to be a fundamental component in human navigation, it is unclear whether travel direction also plays a primary role. This dissertation sets out to investigate the role of travel direction in the spatial orientation system in the human brain by combining methodologies in psychophysics, neuroimaging, and computational modeling.

The first study employs a motion adaptation paradigm from visual neuroscience designed to preclude the contribution of head direction. I found high-level aftereffects of perceived travel direction, indicating that travel direction is indeed a fundamental component of human navigation. Interestingly, I discovered a higher frequency of reporting perceived travel toward the adapted direction, as compared to a no-adapt control - an aftereffect which runs contrary to low-level motion aftereffects. This travel aftereffect was maintained after controlling for possible response biases and approaching effects, and it scaled with adaptation duration. These findings represent the first evidence for a pure travel direction signal in humans, independent of head direction.

The second study examines if, when moving to the brain activation level, it is still possible to discriminate between directions using fMRI signals from distributed brain areas, while people navigate complex environments. Using machine learning methods, I discriminated between head and travel directions - i.e., translational movement directions, rotational movement directions, and stationary facing directions - from those fMRI signals, in a study where people were tasked with actively navigating a complex maze. It is worth noting here that while I did not study head and travel direction signals in isolation from one another, my analysis is informative for our understanding of how the human brain represents spatial orientation. The regions of interest (ROIs) primarily include areas in which head direction signals have been previously reported, including the thalamus, retrosplenial cortex, precuneus, extrastriate cortex, and early visual cortex. I also examined signals from the striatum - i.e., caudate, putamen, nucleus accumbens, and pallidum - along with the hippocampus, amygdala, and the auditory cortex. In addition to the present cognitive map, my model was able to classify directions for future and past directions across ROIs during the stationary period. Interestingly, I only observed correlations between classification accuracy and navigation performance during the test phase, but not during the exploration phase. Transitioning from the exploration phase to the test phase, although there was a tendency to rely more on the allocentric frame of reference for navigation, successful navigation seems to rely more on efficient utilization of the egocentric frame of reference. This relationship was found when looking at the past and future movements, which constitute the travel trajectory and could indicate path planning. The results not only shed light on different directional representations in a distributed head and travel direction system during active navigation in a complex environment, they also support the dynamic involvement of both allocentric and egocentric frames of reference, the representations of past, present, and future cognitive maps, as well as individual differences in fMRI signals that relates to navigation performance.

To understand how the travel direction system might work in the human brain, the third study adopted the experimental paradigm from the first study by building a biologically plausible computational model to simulate the travel direction system. The model predicted the motion aftereffects that I observed experimentally, and was tested with a series of perturbation studies, which brought further support to our understanding of the travel direction system. This study proposed a new approach to simulate the human orientation system by using a recurrent neural network (echo state network).

In summary, I investigated travel direction in human navigation using a combination of psychophysics, neuroimaging, and computational modeling approaches. Each study added an additional level of understanding for travel direction with a different approach. Study 1 provides evidence of what is the role of travel direction in the internal orientation system of human navigation. Study 2 features a distributed travel and head direction system in discriminating directions in a complex navigation task, suggesting where in the human brain travel directions could be represented. Study 3 continues exploring travel direction by demonstrating how the travel direction system might work in the human brain using a computational model. This dissertation suggests a fundamental role of the travel direction system in the human brain, and also illustrates the importance of using multifaceted approaches in understanding neuroscience.