Perceptual precision of passive body tilt is consistent with statistically optimal cue integration

Bayesian optimal adaptation explains age-related human sensorimotor changes

The brain uses information from different sensory systems to guide motor behavior, and aging is associated with simultaneous decline in the quality of sensory information provided to the brain and deterioration in motor control. Correlations between age-dependent decline in sensory anatomical structures and behavior have been demonstrated in many sensorimotor systems, and it has recently been suggested that a Bayesian framework could explain these relationships. Here we show that age-dependent changes in a human sensorimotor reflex, the vestibuloocular reflex, are explained by a Bayesian optimal adaptation in the brain occurring in response to death of motion-sensing hair cells. Specifically, we found that the temporal dynamics of the reflex as a function of age emerge from ( r = 0.93, P < 0.001) a Kalman filter model that determines the optimal behavioral output when the sensory signal-to-noise characteristics are degraded by death of the transducers. These findings demonstrate that the aging brain is capable of generating the ideal and statistically optimal behavioral response when provided with deteriorating sensory information. While the Bayesian framework has been shown to be a general neural principle for multimodal sensory integration and dynamic sensory estimation, these findings provide evidence of longitudinal Bayesian processing over the human life span. These results illuminate how the aging brain strives to optimize motor behavior when faced with deterioration in the peripheral and central nervous systems and have implications in the field of vestibular and balance disorders, as they will likely provide guidance for physical therapy and for prosthetic aids that aim to reduce falls in the elderly. NEW & NOTEWORTHY We showed that age-dependent changes in the vestibuloocular reflex are explained by a Bayesian optimal adaptation in the brain that occurs in response to age-dependent sensory anatomical changes. This demonstrates that the brain can longitudinally respond to age-related sensory loss in an ideal and statistically optimal way. This has implications for understanding and treating vestibular disorders caused by aging and provides insight into the structure-function relationship during aging.

Multivariate Analyses of Balance Test Performance, Vestibular Thresholds, and Age

We previously published vestibular perceptual thresholds and performance in the Modified Romberg Test of Standing Balance in 105 healthy humans ranging from ages 18 to 80 (1). Self-motion thresholds in the dark included roll tilt about an earth-horizontal axis at 0.2 and 1 Hz, yaw rotation about an earth-vertical axis at 1 Hz, y-translation (interaural/lateral) at 1 Hz, and z-translation (vertical) at 1 Hz. In this study, we focus on multiple variable analyses not reported in the earlier study. Specifically, we investigate correlations (1) among the five thresholds measured and (2) between thresholds, age, and the chance of failing condition 4 of the balance test, which increases vestibular reliance by having subjects stand on foam with eyes closed. We found moderate correlations (0.30–0.51) between vestibular thresholds for different motions, both before and after using our published aging regression to remove age effects. We found that lower or higher thresholds across all threshold measures are an individual trait that account for about 60% of the variation in the population. This can be further distributed into two components with about 20% of the variation explained by aging and 40% of variation explained by a single principal component that includes similar contributions from all threshold measures. When only roll tilt 0.2 Hz thresholds and age were analyzed together, we found that the chance of failing condition 4 depends significantly on both (p = 0.006 and p = 0.013, respectively). An analysis incorporating more variables found that the chance of failing condition 4 depended significantly only on roll tilt 0.2 Hz thresholds (p = 0.046) and not age (p = 0.10), sex nor any of the other four threshold measures, suggesting that some of the age effect might be captured by the fact that vestibular thresholds increase with age. For example, at 60 years of age, the chance of failing is roughly 5% for the lowest roll tilt thresholds in our population, but this increases to 80% for the highest roll tilt thresholds. These findings demonstrate the importance of roll tilt vestibular cues for balance, even in individuals reporting no vestibular symptoms and with no evidence of vestibular dysfunction.

A unified internal model theory to resolve the paradox of active versus passive self-motion sensation

Brainstem and cerebellar neurons implement an internal model to accurately estimate self-motion during externally generated (‘passive’) movements. However, these neurons show reduced responses during self-generated (‘active’) movements, indicating that predicted sensory consequences of motor commands cancel sensory signals. Remarkably, the computational processes underlying sensory prediction during active motion and their relationship to internal model computations during passive movements remain unknown. We construct a Kalman filter that incorporates motor commands into a previously established model of optimal passive self-motion estimation. The simulated sensory error and feedback signals match experimentally measured neuronal responses during active and passive head and trunk rotations and translations. We conclude that a single sensory internal model can combine motor commands with vestibular and proprioceptive signals optimally. Thus, although neurons carrying sensory prediction error or feedback signals show attenuated modulation, the sensory cues and internal model are both engaged and critically important for accurate self-motion estimation during active head movements.

When seated in a car, we can detect when the vehicle begins to move even with our eyes closed. Structures in the inner ear called the vestibular, or balance, organs enable us to sense our own movement. They do this by detecting head rotations, accelerations and gravity. They then pass this information on to specialized vestibular regions of the brain.

Experiments using rotating chairs and moving platforms have shown that passive movements – such as car journeys and rollercoaster rides – activate the brain’s vestibular regions. But recent work has revealed that voluntary movements – in which individuals start the movement themselves – activate these regions far less than passive movements. Does this mean that the brain ignores signals from the inner ear during voluntary movements? Another possibility is that the brain predicts in advance how each movement will affect the vestibular organs in the inner ear. It then compares these predictions with the signals it receives during the movement. Only mismatches between the two activate the brain’s vestibular regions.

To test this theory, Laurens and Angelaki created a mathematical model that compares predicted signals with actual signals in the way the theory proposes. The model accurately predicts the patterns of brain activity seen during both active and passive movement. This reconciles the results of previous experiments on active and passive motion. It also suggests that the brain uses similar processes to analyze vestibular signals during both types of movement.

These findings can help drive further research into how the brain uses sensory signals to refine our everyday movements. They can also help us understand how people recover from damage to the vestibular system. Most patients with vestibular injuries learn to walk again, but have difficulty walking on uneven ground. They also become disoriented by passive movement. Using the model to study how the brain adapts to loss of vestibular input could lead to new strategies to aid recovery.

Unbounded evidence accumulation characterizes subjective visual vertical forced-choice perceptual choice and confidence

Humans can subjectively yet quantitatively assess choice confidence based on perceptual precision even when a perceptual decision is made without an immediate reward or feedback. However, surprisingly little is known about choice confidence. Here we investigate the dynamics of choice confidence by merging two parallel conceptual frameworks of decision making, signal detection theory and sequential analyses (i.e., drift-diffusion modeling). Specifically, to capture end-point statistics of binary choice and confidence, we built on a previous study that defined choice confidence in terms of psychophysics derived from signal detection theory. At the same time, we augmented this mathematical model to include accumulator dynamics of a drift-diffusion model to characterize the time dependence of the choice behaviors in a standard forced-choice paradigm in which stimulus duration is controlled by the operator. Human subjects performed a subjective visual vertical task, simultaneously reporting binary orientation choice and probabilistic confidence. Both binary choice and confidence experimental data displayed statistics and dynamics consistent with both signal detection theory and evidence accumulation, respectively. Specifically, the computational simulations showed that the unbounded evidence accumulator model fits the confidence data better than the classical bounded model, while bounded and unbounded models were indistinguishable for binary choice data. These results suggest that the brain can utilize mechanisms consistent with signal detection theory-especially when judging confidence without time pressure.NEW & NOTEWORTHY We found that choice confidence data show dynamics consistent with evidence accumulation for a forced-choice subjective visual vertical task. We also found that the evidence accumulation appeared unbounded when judging confidence, which suggests that the brain utilizes mechanisms consistent with signal detection theory to determine choice confidence.

The Impact of Oral Promethazine on Human Whole-Body Motion Perceptual Thresholds

Despite the widespread treatment of motion sickness symptoms using drugs and the involvement of the vestibular system in motion sickness, little is known about the effects of anti-motion sickness drugs on vestibular perception. In particular, the impact of oral promethazine, widely used for treating motion sickness, on vestibular perceptual thresholds has not previously been quantified. We examined whether promethazine (25 mg) alters vestibular perceptual thresholds in a counterbalanced, double-blind, within-subject study. Thresholds were determined using a direction recognition task (left vs. right) for whole-body yaw rotation, y-translation (interaural), and roll tilt passive, self-motions. Roll tilt thresholds were 31 % higher after ingestion of promethazine (P = 0.005). There were no statistically significant changes in yaw rotation and y-translation thresholds. This worsening of precision could have functional implications, e.g., during driving, bicycling, and piloting tasks. Differing results from some past studies of promethazine on the vestibulo-ocular reflex emphasize the need to study motion perception in addition to motor responses.