Aberrant causal inference and presence of a compensatory mechanism in autism spectrum disorder.

Autism spectrum disorder (ASD) is characterized by a panoply of social, communicative, and sensory anomalies. As such, a central goal of computational psychiatry is to ascribe the heterogenous phenotypes observed in ASD to a limited set of canonical computations that may have gone awry in the disorder. Here, we posit causal inference - the process of inferring a causal structure linking sensory signals to hidden world causes - as one such computation.

Causal inference accounts for heading perception in the presence of object motion.

The brain infers our spatial orientation and properties of the world from ambiguous and noisy sensory cues. Judging self-motion (heading) in the presence of independently moving objects poses a challenging inference problem because the image motion of an object could be attributed to movement of the object, self-motion, or some combination of the two. We test whether perception of heading and object motion follows predictions of a normative causal inference framework.

Bayesian comparison of explicit and implicit causal inference strategies in multisensory heading perception.

The precision of multisensory perception improves when cues arising from the same cause are integrated, such as visual and vestibular heading cues for an observer moving through a stationary environment. In order to determine how the cues should be processed, the brain must infer the causal relationship underlying the multisensory cues. In heading perception, however, it is unclear whether observers follow the Bayesian strategy, a simpler non-Bayesian heuristic, or even perform causal inference at all.

Multisensory Integration of Visual and Vestibular Signals Improves Heading Discrimination in the Presence of a Moving Object.

Unlabelled: Humans and animals are fairly accurate in judging their direction of self-motion (i.e., heading) from optic flow when moving through a stationary environment.

Multisensory self-motion compensation during object trajectory judgments.

Judging object trajectory during self-motion is a fundamental ability for mobile organisms interacting with their environment. This fundamental ability requires the nervous system to compensate for the visual consequences of self-motion in order to make accurate judgments, but the mechanisms of this compensation are poorly understood. We comprehensively examined both the accuracy and precision of observers' ability to judge object trajectory in the world when self-motion was defined by vestibular, visual, or combined visual-vestibular cues.

Estimating distance during self-motion: a role for visual-vestibular interactions.

A fundamental challenge for the visual system is to extract the 3D spatial structure of the environment. When an observer translates without moving the eyes, the retinal speed of a stationary object is related to its distance by a scale factor that depends on the velocity of the observer's self-motion. Here, we aim to test whether the brain uses vestibular cues to self-motion to estimate distance to stationary surfaces in the environment.

Self versus environment motion in postural control.

To stabilize our position in space we use visual information as well as non-visual physical motion cues. However, visual cues can be ambiguous: visually perceived motion may be caused by self-movement, movement of the environment, or both. The nervous system must combine the ambiguous visual cues with noisy physical motion cues to resolve this ambiguity and control our body posture.

Influence of visual scene velocity on segmental kinematics during stance.

We investigated how the velocity of anterior-posterior movement of a visual surround affected segmental kinematics during stance. Ten healthy young adults were exposed to sinusoidal oscillation of an immersive virtual scene at five peak velocities ranging from 1.2 to 188 cm/s at each of four frequencies: 0.