Tracking the Mind’s Eye: Primate Gaze Behavior during Virtual Visuomotor Navigation Reflects Belief Dynamics

Lakshminarasimhan, Kaushik J; Avila, Eric; Neyhart, Erin; DeAngelis, Gregory C.; Pitkow, Xaq; Angelaki, Dora E.

doi:10.1016/j.neuron.2020.02.023

Cited by 42 publications

(98 citation statements)

References 60 publications

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“…Solid lines and dashed lines represent the values obtained To quantify performance accuracy across humans and monkeys, we adopted the approach of receiver operating characteristic (ROC) to continuous responses. Specifically, for each subject, we computed the actual reward rate and the chance level reward rate, obtained by shuffling target locations across trials, as a function of a hypothetical reward window size (Lakshminarasimhan et al, 2020). We obtained the ROC curves by plotting the actual responses against the responses at chance level and computed the area under the ROC curve (AUC) (Fig.…”

Section: Subjects Compensate For Unpredictable Perturbationsmentioning

confidence: 99%

Sensory evidence accumulation using optic flow in a naturalistic navigation task

Alefantis

Lakshminarasimhan

Avila

et al. 2021

Preprint

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Sensory evidence accumulation is considered a hallmark of decision-making in noisy environments. Integration of sensory inputs has been traditionally studied using passive stimuli, segregating perception from action. Lessons learned from this approach, however, may not generalize to ethological behaviors like navigation, where there is an active interplay between perception and action. We designed a sensory-based sequential decision task in virtual reality in which humans and monkeys navigated to a memorized location by integrating optic flow generated by their own joystick movements. A major challenge in such closed-loop tasks is that subjects’ actions will determine future sensory input, causing ambiguity about whether they rely on sensory input rather than expectations based solely on a learned model of the dynamics. To test whether subjects performed sensory integration, we used three independent experimental manipulations: unpredictable optic flow perturbations, which pushed subjects off their trajectory; gain manipulation of the joystick controller, which changed the consequences of actions; and manipulation of the optic flow density, which changed the reliability of sensory evidence. Our results suggest that both macaques and humans relied heavily on optic flow, thereby demonstrating a critical role for sensory evidence accumulation during naturalistic action-perception closed-loop tasks.

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Section: Subjects Compensate For Unpredictable Perturbationsmentioning

confidence: 99%

Sensory evidence accumulation using optic flow in a naturalistic navigation task

Alefantis

Lakshminarasimhan

Avila

et al. 2021

Preprint

Self Cite

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“…Studies have shown that reward circuitry tends to orient the eyes toward the most valuable locations in space [40, 41]. Moreover, when the goal is hidden, it has been argued that fixating the hidden reward zone may allow for the oculomotor circuitry to carry the burden of remembering the latent goal location [42, 43]. Consistent with this, subjects spent a large fraction of time looking at the reward zone (pre-movement: 67±3%, movement: 53±6%).…”

Section: Resultsmentioning

confidence: 99%

Eye movements reveal spatiotemporal dynamics of visually-informed planning in navigation

Zhu

Lakshminarasimhan

Arfaei

et al. 2021

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Goal-oriented navigation is widely understood to depend critically upon internal maps. Although this may be the case in many settings, many animals, such as humans, tend to rely on vision when the environment is complex or unfamiliar. The nature of gaze during visually-guided navigation remains unknown. To study this, we tasked humans to navigate to transiently visible goals in virtual mazes of varying complexity, observing that they achieved near-optimal path lengths in all arenas. By analyzing subjects’ eye movements, we gained insights into the principles of active sensing and prospection that would not have been gleaned from observing navigational behavior alone. The spatial distribution of fixations revealed that environmental complexity mediated a striking trade-off in the extent to which attention was directed towards two complimentary aspects of the world model: the reward location and task-relevant transitions. Furthermore, the temporal evolution of gaze revealed rapid, sequential prospection of the future path, evocative of neural ’preplay’. These findings suggest that the spatiotemporal characteristics of eye movements during navigation are significantly shaped by the unique cognitive computations underlying real-world, sequential decision making.

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“… Churan, von Hopffgarten, and Bremmer (2018) showed that when viewing optic flow stimulus to encode distance traveled, observers showed preferences as to whether they should sample near or farther away from the FOE. Combining an optic flow stimulus with a steering task, Lakshminarasimhan, Avila, Neyhart, DeAngelis, Pitkow, and Angelaki (2020) showed that observers’ eyes tracked an invisible goal for steering rather than the FOE. In real-world eye-tracking during walking or driving, the eyes could track future landing positions of the feet (e.g., Hollands, Marple-Horvat, Henkes, & Rowan, 1995 ; Matthis, Yate, & Hayhoe, 2018 ) or the inner side of the curve before a bend (e.g., Land & Lee, 1994 ).…”

Section: Discussionmentioning

confidence: 99%

Look where you go: Characterizing eye movements toward optic flow

et al. 2021

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When we move through our environment, objects in the visual scene create optic flow patterns on the retina. Even though optic flow is ubiquitous in everyday life, it is not well understood how our eyes naturally respond to it. In small groups of human and non-human primates, optic flow triggers intuitive, uninstructed eye movements to the focus of expansion of the pattern (Knöll, Pillow, & Huk, 2018). Here, we investigate whether such intuitive oculomotor responses to optic flow are generalizable to a larger group of human observers and how eye movements are affected by motion signal strength and task instructions. Observers (N = 43) viewed expanding or contracting optic flow constructed by a cloud of moving dots radiating from or converging toward a focus of expansion that could randomly shift. Results show that 84% of observers tracked the focus of expansion with their eyes without being explicitly instructed to track. Intuitive tracking was tuned to motion signal strength: Saccades landed closer to the focus of expansion, and smooth tracking was more accurate when dot contrast, motion coherence, and translational speed were high. Under explicit tracking instruction, the eyes aligned with the focus of expansion more closely than without instruction. Our results highlight the sensitivity of intuitive eye movements as indicators of visual motion processing in dynamic contexts.

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Tracking the Mind’s Eye: Primate Gaze Behavior during Virtual Visuomotor Navigation Reflects Belief Dynamics

Cited by 42 publications

References 60 publications

Sensory evidence accumulation using optic flow in a naturalistic navigation task

Sensory evidence accumulation using optic flow in a naturalistic navigation task

Eye movements reveal spatiotemporal dynamics of visually-informed planning in navigation

Look where you go: Characterizing eye movements toward optic flow

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