Bistable perception alternates between internal and external modes of sensory processing

Bistable perception, precision and neuromodulation

Bistable perception follows from observing a static, ambiguous, (visual) stimulus with two possible interpretations. Here, we present an active (Bayesian) inference account of bistable perception and posit that perceptual transitions between different interpretations (i.e. inferences) of the same stimulus ensue from specific eye movements that shift the focus to a different visual feature. Formally, these inferences are a consequence of precision control that determines how confident beliefs are and change the frequency with which one can perceive-and alternate between-two distinct percepts. We hypothesized that there are multiple, but distinct, ways in which precision modulation can interact to give rise to a similar frequency of bistable perception. We validated this using numerical simulations of the Necker cube paradigm and demonstrate the multiple routes that underwrite the frequency of perceptual alternation. Our results provide an (enactive) computational account of the intricate precision balance underwriting bistable perception. Importantly, these precision parameters can be considered the computational homologs of particular neurotransmitters-i.e. acetylcholine, noradrenaline, dopamine-that have been previously implicated in controlling bistable perception, providing a computational link between the neurochemistry and perception.

Probabilistic integration of preceding responses explains response bias in perceptual decision making

Expectations of sensory information change not only how well but also what we perceive. Even in an unpredictable environment, the brain is by default constantly engaged in computing probabilities between sensory events. These estimates are used to generate predictions about future sensory events. Here, we investigated the predictability of behavioral responses using three different learning models in three different one-interval two-alternative forced choice experiments with either auditory, vestibular, or visual stimuli. Results indicate that recent decisions, instead of the sequence of generative stimuli, cause serial dependence. By bridging the gap between sequence learning and perceptual decision making, we provide a novel perspective on sequential choice effects. We propose that serial biases reflect the tracking of statistical regularities of the decision variable, offering a broader understanding of this phenomenon.

Conscious interpretation: A distinct aspect for the neural markers of the contents of consciousness

Progress in the science of consciousness depends on the experimental paradigms and varieties of contrastive analysis available to researchers. Here we highlight paradigms where the object is represented in consciousness as a set of its features but the interpretation of this set alternates in consciousness. We group experimental paradigms with this property under the label "conscious interpretation". We compare the paradigms studying conscious interpretation of the already consciously perceived objects with other types of experimental paradigms. We review previous and recent studies investigating this interpretative aspect of consciousness and propose future directions. We put forward the hypothesis that there are types of stimuli with a hierarchy of interpretations for which the rule applies: conscious experience is drawn towards higher-level interpretation and reverting back to the lower level of interpretation is impossible. We discuss how theories of consciousness might incorporate knowledge and constraints arising from the characteristics of conscious interpretation.

Mice alternate between discrete strategies during perceptual decision-making

Classical models of perceptual decision-making assume that subjects use a single, consistent strategy to form decisions, or that decision-making strategies evolve slowly over time. Here we present new analyses suggesting that this common view is incorrect. We analyzed data from mouse and human decision-making experiments and found that choice behavior relies on an interplay among multiple interleaved strategies. These strategies, characterized by states in a hidden Markov model, persist for tens to hundreds of trials before switching, and often switch multiple times within a session. The identified decision-making strategies were highly consistent across mice and comprised a single 'engaged' state, in which decisions relied heavily on the sensory stimulus, and several biased states in which errors frequently occurred. These results provide a powerful alternate explanation for 'lapses' often observed in rodent behavioral experiments, and suggest that standard measures of performance mask the presence of major changes in strategy across trials.

Temporal Visual Patterns of Construction Hazard Recognition Strategies

Visual cognitive strategies in construction hazard recognition (CHR) signifies prominent value for the development of CHR computer vision techniques and safety training. Nonetheless, most studies are based on either sparse fixations or cross-sectional (accumulative) statistics, which lack consideration of temporality and yielding limited visual pattern information. This research aims to investigate the temporal visual search patterns for CHR and the cognitive strategies they imply. An experimental study was designed to simulate CHR and document participants’ visual behavior. Temporal qualitative comparative analysis (TQCA) was applied to analyze the CHR visual sequences. The results were triangulated based on post-event interviews and show that: (1) In the potential electrical contact hazards, the intersection of the energy-releasing source and wire that reflected their interaction is the cognitively driven visual area that participants tend to prioritize; (2) in the PPE-related hazards, two different visual strategies, i.e., “scene-related” and “norm-guided”, can usually be generalized according to the participants’ visual cognitive logic, corresponding to the bottom-up (experience oriented) and top-down (safety knowledge oriented) cognitive models. This paper extended recognition-by-components (RBC) model and gestalt model as well as providing feasible practical guide for safety trainings and theoretical foundations of computer vision techniques for CHR.