scholarly journals Circular inference in bistable perception

2019 ◽  
Author(s):  
Pantelis Leptourgos ◽  
Charles-Edouard Notredame ◽  
Marion Eck ◽  
Renaud Jardri ◽  
Sophie Denève
Keyword(s):  
Prior Knowledge ◽  
Bayesian Approach ◽  
Necker Cube ◽  
Top Down ◽  
Inference Model ◽  
Bottom Up ◽  
Bistable Perception ◽  
Sensory Evidence ◽  
The Brain ◽  
Healthy Participants

AbstractWhen facing fully ambiguous images, the brain cannot commit to a single percept and instead switches between mutually exclusive interpretations every few seconds, a phenomenon known as bistable perception. Despite years of research, there is still no consensus on whether bistability, and perception in general, is driven primarily by bottom-up or top-down mechanisms. Here, we adopted a Bayesian approach in an effort to reconcile these two theories. Fifty-five healthy participants were exposed to an adaptation of the Necker cube paradigm, in which we manipulated sensory evidence (by shadowing the cube) and prior knowledge (e.g., by varying instructions about what participants should expect to see). We found that manipulations of both sensory evidence and priors significantly affected the way participants perceived the Necker cube. However, we observed an interaction between the effect of the cue and the effect of the instructions, a finding incompatible with Bayes-optimal integration. In contrast, the data were well predicted by a circular inference model. In this model, ambiguous sensory evidence is systematically biased in the direction of current expectations, ultimately resulting in a bistable percept.

scholarly journals Shift toward prior knowledge confers a perceptual advantage in early psychosis and psychosis-prone healthy individuals

2015 ◽  
Vol 112 (43) ◽  
pp. 13401-13406 ◽  
Author(s):  
Christoph Teufel ◽  
Naresh Subramaniam ◽  
Veronika Dobler ◽  
Jesus Perez ◽  
Johanna Finnemann ◽  
...  
Keyword(s):  
Information Processing ◽  
Prior Knowledge ◽  
Early Psychosis ◽  
Psychotic Symptoms ◽  
Psychotic Experiences ◽  
Healthy Individuals ◽  
Top Down ◽  
Bottom Up ◽  
Psychosis Proneness ◽  
Sensory Evidence

Many neuropsychiatric illnesses are associated with psychosis, i.e., hallucinations (perceptions in the absence of causative stimuli) and delusions (irrational, often bizarre beliefs). Current models of brain function view perception as a combination of two distinct sources of information: bottom-up sensory input and top-down influences from prior knowledge. This framework may explain hallucinations and delusions. Here, we characterized the balance between visual bottom-up and top-down processing in people with early psychosis (study 1) and in psychosis-prone, healthy individuals (study 2) to elucidate the mechanisms that might contribute to the emergence of psychotic experiences. Through a specialized mental-health service, we identified unmedicated individuals who experience early psychotic symptoms but fall below the threshold for a categorical diagnosis. We observed that, in early psychosis, there was a shift in information processing favoring prior knowledge over incoming sensory evidence. In the complementary study, we capitalized on subtle variations in perception and belief in the general population that exhibit graded similarity with psychotic experiences (schizotypy). We observed that the degree of psychosis proneness in healthy individuals, and, specifically, the presence of subtle perceptual alterations, is also associated with stronger reliance on prior knowledge. Although, in the current experimental studies, this shift conferred a performance benefit, under most natural viewing situations, it may provoke anomalous perceptual experiences. Overall, we show that early psychosis and psychosis proneness both entail a basic shift in visual information processing, favoring prior knowledge over incoming sensory evidence. The studies provide complementary insights to a mechanism by which psychotic symptoms may emerge.

Perceptual inferences in schizophrenia: A preliminary study on healthy participants

2015 ◽  
Vol 30 (S2) ◽  
pp. S113-S114 ◽  
Author(s):  
P. Leptourgos ◽  
C.E. Notredame ◽  
R. Jardri ◽  
S. Denève
Keyword(s):  
Visual Cues ◽  
Necker Cube ◽  
Psychotic Symptoms ◽  
Bistable Perception ◽  
Sensory Evidence ◽  
Preliminary Study ◽  
Dynamic Measures ◽  
Perceptual Systems ◽  
Healthy Participants ◽  
Inference Task

Recently, Jardri and Denève proposed that positive symptoms in schizophrenia could be generated by an imbalance between excitation and inhibition in brain networks, which leads to circular inference, an aberrant form of inference where messages (bottom up and/or top down) are counted more than once and thus, are overweighted [1]. Moreover, they postulated that psychotic symptoms are caused by a system that “expects what it senses” and as a result attributes extreme weight even to weak sensory evidences. Their hypothesis was then validated by a probabilistic inference task (in prep.). Here, we put forward a new experimental study that could validate the circular inference framework in the domain of visual perception. Initially, we restricted ourselves to healthy controls, whose tendencies for psychotic symptoms were measured using appropriate scales. We investigated the computations performed by perceptual systems when facing ambiguous sensory evidence. In those cases, perception is known to oscillate between two interpretations, a phenomenon known as bistable perception. More specifically, we asked how prior expectations and visual cues affect the dynamics of bistability. Participants looked at a Necker cube that was continuously displayed on the screen and reported their percept every time they heard a sound [2]. We manipulated sensory evidence by adding shades to the stimuli and prior expectations by giving different instructions concerning the presence of an implicit bias [3]. We showed that both prior expectations and visual cues significantly affect bistability, using both static and dynamic measures. We also found that the behavior could be well fitted by Bayesian models (“simple” Bayes, hierarchical Bayesian model with Markovian statistics). Preliminary results from patients will also be presented.

Gamma response of the brain: a multifunctional oscillation that represents bottom-up with top-down processing

2001 ◽  
Vol 39 (2-3) ◽  
pp. 137-150 ◽  
Author(s):  
S Karakaş ◽  
C Başar-Eroğlu ◽  
Ç Özesmi ◽  
H Kafadar ◽  
Ö.Ü Erzengin
Keyword(s):  
Top Down ◽  
Bottom Up ◽  
The Brain

Top-Down Predictions Determine Perceptions

2017 ◽  
Author(s):  
Martin V. Butz ◽  
Esther F. Kutter
Keyword(s):  
Graphical Models ◽  
Information Integration ◽  
Visual Processing ◽  
Visual Information ◽  
Generative Models ◽  
Sources Of Information ◽  
Multiple Sources ◽  
Top Down ◽  
Bottom Up ◽  
The Brain

While bottom-up visual processing is important, the brain integrates this information with top-down, generative expectations from very early on in the visual processing hierarchy. Indeed, our brain should not be viewed as a classification system, but rather as a generative system, which perceives something by integrating sensory evidence with the available, learned, predictive knowledge about that thing. The involved generative models continuously produce expectations over time, across space, and from abstracted encodings to more concrete encodings. Bayesian information processing is the key to understand how information integration must work computationally – at least in approximation – also in the brain. Bayesian networks in the form of graphical models allow the modularization of information and the factorization of interactions, which can strongly improve the efficiency of generative models. The resulting generative models essentially produce state estimations in the form of probability densities, which are very well-suited to integrate multiple sources of information, including top-down and bottom-up ones. A hierarchical neural visual processing architecture illustrates this point even further. Finally, some well-known visual illusions are shown and the perceptions are explained by means of generative, information integrating, perceptual processes, which in all cases combine top-down prior knowledge and expectations about objects and environments with the available, bottom-up visual information.

ARTISTIC COMPLEXITY AND SALIENCY: TWO FACES OF THE SAME COIN?

2013 ◽  
Vol 09 (02) ◽  
pp. 1350010 ◽  
Author(s):  
MATTEO CACCIOLA ◽  
GIANLUIGI OCCHIUTO ◽  
FRANCESCO CARLO MORABITO
Keyword(s):  
Information Content ◽  
Visual Saliency ◽  
Relevant Information ◽  
Human Observer ◽  
Top Down ◽  
Complexity Measures ◽  
Bottom Up ◽  
Content Description ◽  
Brain Processing ◽  
The Brain

Many computer vision problems consist of making a suitable content description of images usually aiming to extract the relevant information content. In case of images representing paintings or artworks, the information extracted is rather subject-dependent, thus escaping any universal quantification. However, we proposed a measure of complexity of such kinds of oeuvres which is related to brain processing. The artistic complexity measures the brain inability to categorize complex nonsense forms represented in modern art, in a dynamic process of acquisition that most involves top-down mechanisms. Here, we compare the quantitative results of our analysis on a wide set of paintings of various artists to the cues extracted from a standard bottom-up approach based on visual saliency concept. In every painting inspection, the brain searches for more informative areas at different scales, then connecting them in an attempt to capture the full impact of information content. Artistic complexity is able to quantify information which might have been individually lost in the fruition of a human observer thus identifying the artistic hand. Visual saliency highlights the most salient areas of the paintings standing out from their neighbours and grabbing our attention. Nevertheless, we will show that a comparison on the ways the two algorithms act, may manifest some interesting links, finally indicating an interplay between bottom-up and top-down modalities.

scholarly journals The cutaneous borders of interoception: Active and social inference of pain and pleasure on the skin

2018 ◽  
Author(s):  
Mariana von Mohr ◽  
Aikaterini Fotopoulou
Keyword(s):  
Social Factors ◽  
Predictive Coding ◽  
Active Inference ◽  
Top Down ◽  
Bottom Up ◽  
Social Inference ◽  
Brain Levels ◽  
The Brain

Pain and pleasant touch have been recently classified as interoceptive modalities. This reclassification lies at the heart of long-standing debates questioning whether these modalities should be defined as sensations on their basis of neurophysiological specificity at the periphery or as homeostatic emotions on the basis of top-down convergence and modulation at the spinal and brain levels. Here, we outline the literature on the peripheral and central neurophysiology of pain and pleasant touch. We next recast this literature within a recent Bayesian predictive coding framework, namely active inference. This recasting puts forward a unifying model of bottom-up and top-down determinants of pain and pleasant touch and the role of social factors in modulating the salience of peripheral signals reaching the brain.

scholarly journals Can noises defeat will power in Necker cube reversals? Equating top-down influence with bottom-up bias with a noise paradigm

2010 ◽  
Vol 8 (6) ◽  
pp. 255-255
Author(s):  
S. H.-L. Chien ◽  
J.-C. Chen ◽  
C.-C. Chen
Keyword(s):  
Necker Cube ◽  
Top Down ◽  
Bottom Up ◽  
Will Power

scholarly journals The Curious Incident of Attention in Multisensory Integration: Bottom-up vs. Top-down

2016 ◽  
Vol 29 (6-7) ◽  
pp. 557-583 ◽  
Author(s):  
Emiliano Macaluso ◽  
Uta Noppeney ◽  
Durk Talsma ◽  
Tiziana Vercillo ◽  
Jess Hartcher-O’Brien ◽  
...  
Keyword(s):  
Prior Knowledge ◽  
Multisensory Integration ◽  
The Other ◽  
Top Down ◽  
Bottom Up ◽  
Stimulus Properties ◽  
Low Level ◽  
Other Hand ◽  
Current Task ◽  
The One

The role attention plays in our experience of a coherent, multisensory world is still controversial. On the one hand, a subset of inputs may be selected for detailed processing and multisensory integration in a top-down manner, i.e., guidance of multisensory integration by attention. On the other hand, stimuli may be integrated in a bottom-up fashion according to low-level properties such as spatial coincidence, thereby capturing attention. Moreover, attention itself is multifaceted and can be describedviaboth top-down and bottom-up mechanisms. Thus, the interaction between attention and multisensory integration is complex and situation-dependent. The authors of this opinion paper are researchers who have contributed to this discussion from behavioural, computational and neurophysiological perspectives. We posed a series of questions, the goal of which was to illustrate the interplay between bottom-up and top-down processes in various multisensory scenarios in order to clarify the standpoint taken by each author and with the hope of reaching a consensus. Although divergence of viewpoint emerges in the current responses, there is also considerable overlap: In general, it can be concluded that the amount of influence that attention exerts on MSI depends on the current task as well as prior knowledge and expectations of the observer. Moreover stimulus properties such as the reliability and salience also determine how open the processing is to influences of attention.

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