Andrew William Ellis

Internal Models, Vestibular Cognition, and Mental Imagery: Conceptual Considerations.

Vestibular cognition has recently gained attention. Despite numerous experimental and clinical demonstrations, it is not yet clear what vestibular cognition really is. For future research in vestibular cognition, adopting a computational approach will make it easier to explore the underlying mechanisms. Indeed, most modeling approaches in vestibular science include a top-down or a priori component. We review recent Bayesian optimal observer models, and discuss in detail the conceptual value of prior assumptions, likelihood and posterior estimates for research in vestibular cognition. We then consider forward models in vestibular processing, which are required in order to distinguish between sensory input that is induced by active self-motion, and sensory input that is due to passive self-motion. We suggest that forward models are used not only in the service of estimating sensory states but they can also be drawn upon in an offline mode (e.g., spatial perspective transformations), in which interaction with sensory input is not desired. A computational approach to vestibular cognition will help to discover connections across studies, and it will provide a more coherent framework for investigating vestibular cognition.

Negative emotional stimuli enhance vestibular processing

Recent studies have shown that vestibular stimulation can influence affective processes. In the present study, we examined whether emotional information can also modulate vestibular perception. Participants performed a vestibular discrimination task on a motion platform while viewing emotional pictures. Six different picture categories were taken from the International Affective Picture System: mutilation, threat, snakes, neutral objects, sports, and erotic pictures. Using a Bayesian hierarchical approach, we were able to show that vestibular discrimination improved when participants viewed emotionally negative pictures (mutilation, threat, snake) when compared to neutral/positive objects. We conclude that some of the mechanisms involved in the processing of vestibular information are also sensitive to emotional content. Emotional information signals importance and mobilizes the body for action. In case of danger, a successful motor response requires precise vestibular processing. Therefore, negative emotional information improves processing of vestibular information.

Toward a Dynamic Probabilistic Model for Vestibular Cognition

We suggest that research in vestibular cognition will benefit from the theoretical framework of probabilistic models. This will aid in developing an understanding of how interactions between high-level cognition and low-level sensory processing might occur. Many such interactions have been shown experimentally; however, to date, no attempt has been made to systematically explore vestibular cognition by using computational modeling. It is widely assumed that mental imagery and perception share at least in part neural circuitry, and it has been proposed that mental simulation is closely connected to the brain’s ability to make predictions. We claim that this connection has been disregarded in the vestibular domain, and we suggest ways in which future research may take this into consideration.

Vestibular cognition: the effect of prior belief on vestibular perceptual decision making

Vestibular cognition is a growing field of interest and relatively little is known about the underlying mechanisms. We tested the effect of prior beliefs about the relative probability (50:50 vs. 80:20) of motion direction (yaw rotation) using a direction discrimination task. We analyzed choices individually with a logistic regression model and together with response times using a cognitive process model. The results show that self-motion perception is altered by prior belief, leading to a shift of the psychometric function, without a loss of sensitivity. Hierarchical drift diffusion analysis showed that at the group level, prior belief manifests itself as an offset to the drift criterion. However, individual model fits revealed that participants vary in how they use cognitive information in perceptual decision making. At the individual level, the response bias induced by a prior belief resulted either in a change in starting point (prior to evidence accumulation) or drift rate (during evidence accumulation). Participants incorporate prior belief in a self-motion discrimination task, albeit in different ways.

Cognitive Rehabilitation In Bilateral Vestibular Patients: A Computational Perspective

There is evidence that vestibular sensory processing affects, and is affected by, higher cognitive processes. This is highly relevant from a clinical perspective, where there is evidence for cognitive impairments in patients with peripheral vestibular deficits. The vestibular system performs complex probabilistic computations, and we claim that understanding these is important for investigating interactions between vestibular processing and cognition. Furthermore, this will aid our understanding of patients’ self-motion perception and will provide useful information for clinical interventions. We propose that cognitive training is a promising way to alleviate the debilitating symptoms of patients with complete bilateral vestibular loss (BVP), who often fail to show improvement when relying solely on conventional treatment methods. We present a probabilistic model capable of processing vestibular sensory data during both passive and active self-motion. Crucially, in our model, knowledge from multiple sources, including higher-level cognition, can be used to predict head motion. This is the entry point for cognitive interventions. Despite the loss of sensory input, the processing circuitry in BVP patients is still intact, and they can still perceive self-motion when the movement is self-generated. We provide computer simulations illustrating self-motion perception of BVP patients. Cognitive training may lead to more accurate and confident predictions, which result in decreased weighting of sensory input, and thus improved self-motion perception. Using our model, we show the possible impact of cognitive interventions to help vestibular rehabilitation in patients with BVP.

Balance ist mehr als ein Kinderspiel

Der Gleichgewichtssinn orientiere den Menschen nur uber seine Lage im Raum, dachte man bisher. Doch jetzt weiss man: Er steckt voller Geheimnisse und hat sogar Einfluss auf unsere kognitiven Fahigkeiten.

Source Memory for Mental Imagery: Influences of the Stimuli’s Ease of Imagery

The present study investigated how ease of imagery influences source monitoring accuracy. Two experiments were conducted in order to examine how ease of imagery influences the probability of source confusions of perceived and imagined completions of natural symmetric shapes. The stimuli consisted of binary pictures of natural objects, namely symmetric pictures of birds, butterflies, insects, and leaves. The ease of imagery (indicating the similarity of the sources) and the discriminability (indicating the similarity of the items) of each stimulus were estimated in a pretest and included as predictors of the memory performance for these stimuli. It was found that confusion of the sources becomes more likely when the imagery process was relatively easy. However, if the different processes of source monitoring—item memory, source memory and guessing biases—are disentangled, both experiments support the assumption that the effect of decreased source memory for easily imagined stimuli is due to decision processes and misinformation at retrieval rather than encoding processes and memory retention. The data were modeled with a Bayesian hierarchical implementation of the one high threshold source monitoring model.

Disentangling mental imagery and perceptual expectation

Mental imagery and perception are thought to rely on similar neural circuits, and many recent behavioral studies have attempted to demonstrate interactions between actual physical stimulation and sensory imagery in the corresponding sensory modality. However, there has been a lack of theoretical understanding of the nature of these interactions, and both interferential and facilitatory effects have been found. Facilitatory effects appear strikingly similar to those that arise due to experimental manipulations of expectation. Using a self-motion discrimination task, we try to disentangle the effects of mental imagery from those of expectation by using a hierarchical drift diffusion model to investigate both choice data and response times. Manipulations of expectation are reasonably well understood in terms of their selective influence on parameters of the drift diffusion model, and in this study, we make the first attempt to similarly characterize the effects of mental imagery. We investigate mental imagery within the computational framework of control theory and state estimation. • Mental imagery and perception are thought to rely on similar neural circuits; however, on more theoretical grounds, imagery seems to be closely related to the output of forward models (sensory predictions). • We reanalyzed data from a study of imagined self-motion. • Bayesian modeling of response times may allow us to disentangle the effects of mental imagery on behavior from other cognitive (top-down) effects, such as expectation.