A predictive coding account of bistable perception - a model-based fMRI study

In bistable vision, subjective perception wavers between two interpretations of a constant ambiguous stimulus. This dissociation between conscious perception and sensory stimulation has motivated various empirical studies on the neural correlates of bistable perception, but the neurocomputational mechanism behind endogenous perceptual transitions has remained elusive. Here, we recurred to a generic Bayesian framework of predictive coding and devised a model that casts endogenous perceptual transitions as a consequence of prediction errors emerging from residual evidence for the suppressed percept. Data simulations revealed close similarities between the model’s predictions and key temporal characteristics of perceptual bistability, indicating that the model was able to reproduce bistable perception. Fitting the predictive coding model to behavioural data from an fMRI-experiment on bistable perception, we found a correlation across participants between the model parameter encoding perceptual stabilization and the behaviourally measured frequency of perceptual transitions, corroborating that the model successfully accounted for participants’ perception. Formal model comparison with established models of bistable perception based on mutual inhibition and adaptation, noise or a combination of adaptation and noise was used for the validation of the predictive coding model against the established models. Most importantly, model-based analyses of the fMRI data revealed that prediction error time-courses derived from the predictive coding model correlated with neural signal time-courses in bilateral inferior frontal gyri and anterior insulae. Voxel-wise model selection indicated a superiority of the predictive coding model over conventional analysis approaches in explaining neural activity in these frontal areas, suggesting that frontal cortex encodes prediction errors that mediate endogenous perceptual transitions in bistable perception. Taken together, our current work provides a theoretical framework that allows for the analysis of behavioural and neural data using a predictive coding perspective on bistable perception. In this, our approach posits a crucial role of prediction error signalling for the resolution of perceptual ambiguities

Data from: Expanding the understanding of local community assembly in adaptive radiations

Communities are thought to be assembled by two types of filters: by the environment relating to the fundamental niche and by biotic interactions relating to the realized niche. Both filters include parameters related to functional traits, and their variation along environmental gradients. Here we infer the general importance of environmental filtering of a functional trait determining local community assembly within insular adaptive radiations on the example of Caribbean Anolis lizards. We constructed maps for the probability of presence of Anolis ecomorphs (ecology-morphology-behavior specialists) on the Greater Antilles and overlaid these to estimate ecomorph community completeness (ECC) over the landscape. We then tested for differences in environmental parameter spaces among islands for real and cross-fitted ECC values to see whether the underlying assembly filters are deterministic (i.e., similar among islands). We then compared information-theoretic models of climatic and landscape parameters among Greater Antillean islands and inferred whether body mass as functional trait determines ECC. We found areas with high ECC to be strongly correlated to environmental filters, partly related to elevation. The environmental parameters influencing high ECC differed among islands. With the exception of the Jamaican twig ecomorph (which we suspect to be misclassified), smaller ecomorphs were more restricted to higher elevations than larger ones which might reflect filtering on the basis of differential physiological restrictions of ecomorphs. Our results in Anolis show that local community assembly within adaptive island radiations of animals can be determined by environmental filtering of functional traits, independently from species composition and realized environmental niche space

Correction: Psychotic Experiences and Overhasty Inferences Are Related to Maladaptive Learning.

[This corrects the article DOI: 10.1371/journal.pcbi.1005328.]

Disentangling composite colour patterns in a poison frog species

A phylogenetic approach was performed to infer whether variation in conspicuous colour-patterns of a poison frog (Dendrobatidae: Dendrobates tinctorius) has evolved neutrally or under selection. Colour and pattern were split into components that were separately analysed and subsequently re-grouped via principal component analysis. This revealed four different 'displayed' factors on the dorsal and lateral views versus one 'concealed' factor on the ventral view. Based on the assumption that current patterns of trait variation contain information about the evolutionary history of the phenotype, we correlated these trait components to a neutrally evolving gene fragment (cytochrome b). The concealed factor was significantly correlated with the marker fragment, which identified it as having evolved under genetic drift. Noncorrelation of all displayed factors with the marker may indicate the evolution of colour patterns on dorsum and flanks under selection. In our example, colour pattern should therefore be regarded as a multicomponent signal system. © 2008 The Linnean Society of London

New host and geographical distribution for the pearlfish Carapus mourlani (Pisces, Carapidae) with a discussion on Carapini nomenclature and biogeography

Specimens of the pearlfish Carapus mourlani (Carapidae) were observed for the first time in association with the sea cucumber Isostichopus fuscus (Holothuroidea: Echinodermata) along the coast of Ecuador. Out of 4345 sea cucumbers collected from various depths between 5 and 60 m, 12 harbored a pearlfish either in the coelomic cavity, the respiratory tree, or the digestive tract, yielding a prevalence of ca. 0.0028. The presence of C. mourlani appeared to be detrimental to the holothurian host in some cases. Side effects resulting from coelomic cavity infections included less advanced gonad maturity (reduced gonadal tubule diameter and length, lower ratio of mature oocytes) and a significant proportion of necrotic and shriveled gonadal tubules, devoid of gametes. Aside from discussing this evidence, the present paper briefly describes the biology of the pearlfish, its relationship with the host, and its daily activity cycle

Overly Strong Priors for Socially Meaningful Visual Signals Are Linked to Psychosis Proneness in Healthy Individuals

According to the predictive coding theory of psychosis, hallucinations and delusions are explained by an overweighing of high-level prior expectations relative to sensory information that leads to false perceptions of meaningful signals. However, it is currently unclear whether the hypothesized overweighing of priors (1) represents a pervasive alteration that extends to the visual modality and (2) takes already effect at early automatic processing stages. Here, we addressed these questions by studying visual perception of socially meaningful stimuli in healthy individuals with varying degrees of psychosis proneness (n = 39). In a first task, we quantified participants' prior for detecting faces in visual noise using a Bayesian decision model. In a second task, we measured participants' prior for detecting direct gaze stimuli that were rendered invisible by continuous flash suppression. We found that the prior for detecting faces in noise correlated with hallucination proneness (r = 0.50, p = 0.001, Bayes factor 1/20.1) as well as delusion proneness (r = 0.46, p = 0.003, BF 1/9.4). The prior for detecting invisible direct gaze was significantly associated with hallucination proneness (r = 0.43, p = 0.009, BF 1/3.8) but not conclusively with delusion proneness (r = 0.30, p = 0.079, BF 1.7). Our results provide evidence for the idea that overly strong high-level priors for automatically detecting socially meaningful stimuli might constitute a processing alteration in psychosis

Learning what to see in a changing world

Visual perception is strongly shaped by expectations, but it is poorly understood how such perceptual expectations are learned in our dynamic sensory environment. Here, we applied a Bayesian framework to investigate whether perceptual expectations are continuously updated from different aspects of ongoing experience. In two experiments, human observers performed an associative learning task in which rapidly changing expectations about the appearance of ambiguous stimuli were induced. We found that perception of ambiguous stimuli was biased by both learned associations and previous perceptual outcomes. Computational modeling revealed that perception was best explained by a model that continuously updated priors from associative learning and perceptual history and combined these priors with the current sensory information in a probabilistic manner. Our findings suggest that the construction of visual perception is a highly dynamic process that incorporates rapidly changing expectations from different sources in a manner consistent with Bayesian learning and inference