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Continuous Psychophysics, which couples a continuous stimulus with a continuous response, is a promising tool to break out of the confines of traditional designs based on discrete trials. In this pre-registered study, we explore to what extent this paradigm is useful in the study of multisensory integration. We expand on Tonelli et al.s (2025) seminal study by additionally examining the role of eye-movements, using a Kalman filter to estimate the sensory noise underlying behavioral tracking parameters and employing a virtual reality set-up. We immersed two cohorts of participants (n = 30 each) in a virtual meadow environment and asked them to continuously track a drone (Experiment 1) or a swarm of flies (Experiment 2) with a controller, while simultaneously recording their eye movements. We manipulated the reliability of visual cues using four levels of fog (from a completely clear view to impenetrable fog where no visual cues to the targets position were available) as well as the presence of sound cues emitted from the object (sound present/absent). The maximum correlation between stimulus and response was higher when sound was present in some conditions, particularly when visual uncertainty was high, while the tracking delay remained unaffected across all fog levels. Using a Kalman filter to estimate the underlying sensory noise, we found strong evidence that sensory noise was lower when sound was present than when sound was absent both for manual and for ocular tracking, particularly for those conditions with higher visual uncertainty. In exploratory analyses, we further show strong correlations between manual and ocular tracking in all measures (maximum correlation, tracking delay, sensory precision). However, when isolating the multisensory advantage, these correlations all but disappeared for maximum correlation and tracking delay, while remaining substantial for sensory precision. Similarly, behavioral tracking correlated generally strongly with underlying sensory noise, but much less so when it came to the advantage conferred by added sound cues. Our results show that continuous psychophysics is well-suited for the study of multisensory integration, particularly when a Kalman filter analysis is used to estimate sensory uncertainty from behavioral data.

Animals are capable of internally modulating behavior as a function of internal state, environmental sensory conditions, and context. Classical models often assume that sensorimotor decisions are driven primarily by external stimuli, with individual biases treated as either constant or evolving monotonically over time. Here, we show that 5-day-old zebrafish larvae display slowly changing directional swim biases even in stable, homogeneous environments, with fluctuations unfolding over many hours. Computational modeling suggests that these biases arise from a non-stationary Markovian process, with two largely independent internal input streams modulating the tendency to repeat swim directions across consecutive swim bouts. These slow fluctuations are present across sensory conditions, including different light intensities and global motion cues, although the switching statistics are modulated by these conditions. Our findings reveal an intrinsic, context-sensitive source of behavioral variability and provide a framework for further study of computational principles that generate spontaneous and adaptive behavior.