scholarly journals Overly strong priors for socially meaningful visual signals in psychosis proneness

2018 ◽  
Author(s):  
Heiner Stuke ◽  
Elisabeth Kress ◽  
Veith Andreas Weilnhammer ◽  
Philipp Sterzer ◽  
Katharina Schmack
Keyword(s):  
Predictive Coding ◽  
Sensory Information ◽  
Auditory Hallucinations ◽  
Visual Signals ◽  
Visual Modality ◽  
Continuous Flash Suppression ◽  
Direct Gaze ◽  
Psychosis Proneness ◽  
High Level ◽  
Meaningful Stimuli

ABSTRACTPredictive coding accounts of psychosis state that an overweighing of high-level priors relative to sensory information may lead to the misperception of meaningful signals underlying the experience of auditory hallucinations and delusions. However, it is currently unclear whether the hypothesized overweighing of priors (1) represents a pervasive alteration that also affects 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. 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 (rho=0.50, p=0.001) as well as delusion proneness (rho=0.44, p=0.005). Similarly, the prior for detecting invisible direct gaze was significantly associated with hallucination proneness (rho = 0.42, p = 0.010) and trend-wise with delusion proneness (rho = 0.29, p = 0.087). Our results provide evidence for the idea that overly strong high-level priors for automatically detecting socially meaningful stimuli might constitute a generic processing alteration in psychosis.

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

2021 ◽  
Vol 12 ◽  
Author(s):  
Heiner Stuke ◽  
Elisabeth Kress ◽  
Veith Andreas Weilnhammer ◽  
Philipp Sterzer ◽  
Katharina Schmack
Keyword(s):  
Bayes Factor ◽  
Sensory Information ◽  
Visual Signals ◽  
Visual Modality ◽  
Bayesian Decision ◽  
Healthy Individuals ◽  
Direct Gaze ◽  
Psychosis Proneness ◽  
High Level ◽  
Meaningful Stimuli

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.

Compressed sensorimotor-to-transmodal hierarchical organization in schizophrenia

2021 ◽  
pp. 1-14
Author(s):  
Debo Dong ◽  
Dezhong Yao ◽  
Yulin Wang ◽  
Seok-Jun Hong ◽  
Sarah Genon ◽  
...  
Keyword(s):  
Sensory Information ◽  
Resting State Fmri ◽  
Brain Regions ◽  
High Order ◽  
Hierarchical Organization ◽  
System Level ◽  
Integrative System ◽  
Sensorimotor Region ◽  
Cortical Hierarchy ◽  
High Level

Abstract Background Schizophrenia has been primarily conceptualized as a disorder of high-order cognitive functions with deficits in executive brain regions. Yet due to the increasing reports of early sensory processing deficit, recent models focus more on the developmental effects of impaired sensory process on high-order functions. The present study examined whether this pathological interaction relates to an overarching system-level imbalance, specifically a disruption in macroscale hierarchy affecting integration and segregation of unimodal and transmodal networks. Methods We applied a novel combination of connectome gradient and stepwise connectivity analysis to resting-state fMRI to characterize the sensorimotor-to-transmodal cortical hierarchy organization (96 patients v. 122 controls). Results We demonstrated compression of the cortical hierarchy organization in schizophrenia, with a prominent compression from the sensorimotor region and a less prominent compression from the frontal−parietal region, resulting in a diminished separation between sensory and fronto-parietal cognitive systems. Further analyses suggested reduced differentiation related to atypical functional connectome transition from unimodal to transmodal brain areas. Specifically, we found hypo-connectivity within unimodal regions and hyper-connectivity between unimodal regions and fronto-parietal and ventral attention regions along the classical sensation-to-cognition continuum (voxel-level corrected, p < 0.05). Conclusions The compression of cortical hierarchy organization represents a novel and integrative system-level substrate underlying the pathological interaction of early sensory and cognitive function in schizophrenia. This abnormal cortical hierarchy organization suggests cascading impairments from the disruption of the somatosensory−motor system and inefficient integration of bottom-up sensory information with attentional demands and executive control processes partially account for high-level cognitive deficits characteristic of schizophrenia.

scholarly journals Perceptual decisions are biased toward relevant prior choices

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Helen Feigin ◽  
Shira Baror ◽  
Moshe Bar ◽  
Adam Zaidel
Keyword(s):  
Sensory Information ◽  
Irrelevant Stimulus ◽  
Stimulus Feature ◽  
Serial Dependence ◽  
Low Level ◽  
Subsequent Test ◽  
Key Factor ◽  
High Level ◽  
Motor Actions ◽  
The Brain

AbstractPerceptual decisions are biased by recent perceptual history—a phenomenon termed 'serial dependence.' Here, we investigated what aspects of perceptual decisions lead to serial dependence, and disambiguated the influences of low-level sensory information, prior choices and motor actions. Participants discriminated whether a brief visual stimulus lay to left/right of the screen center. Following a series of biased ‘prior’ location discriminations, subsequent ‘test’ location discriminations were biased toward the prior choices, even when these were reported via different motor actions (using different keys), and when the prior and test stimuli differed in color. By contrast, prior discriminations about an irrelevant stimulus feature (color) did not substantially influence subsequent location discriminations, even though these were reported via the same motor actions. Additionally, when color (not location) was discriminated, a bias in prior stimulus locations no longer influenced subsequent location discriminations. Although low-level stimuli and motor actions did not trigger serial-dependence on their own, similarity of these features across discriminations boosted the effect. These findings suggest that relevance across perceptual decisions is a key factor for serial dependence. Accordingly, serial dependence likely reflects a high-level mechanism by which the brain predicts and interprets new incoming sensory information in accordance with relevant prior choices.

scholarly journals Neural Correlates of Group Bias During Natural Viewing

2018 ◽  
Vol 29 (8) ◽  
pp. 3380-3389
Author(s):  
Timothy J Andrews ◽  
Ryan K Smith ◽  
Richard L Hoggart ◽  
Philip I N Ulrich ◽  
Andre D Gouws
Keyword(s):  
Time Course ◽  
Social Groups ◽  
Sensory Information ◽  
Brain Regions ◽  
Group Differences ◽  
Neural Basis ◽  
Brain Responses ◽  
The World ◽  
High Level ◽  
The Brain

Abstract Individuals from different social groups interpret the world in different ways. This study explores the neural basis of these group differences using a paradigm that simulates natural viewing conditions. Our aim was to determine if group differences could be found in sensory regions involved in the perception of the world or were evident in higher-level regions that are important for the interpretation of sensory information. We measured brain responses from 2 groups of football supporters, while they watched a video of matches between their teams. The time-course of response was then compared between individuals supporting the same (within-group) or the different (between-group) team. We found high intersubject correlations in low-level and high-level regions of the visual brain. However, these regions of the brain did not show any group differences. Regions that showed higher correlations for individuals from the same group were found in a network of frontal and subcortical brain regions. The interplay between these regions suggests a range of cognitive processes from motor control to social cognition and reward are important in the establishment of social groups. These results suggest that group differences are primarily reflected in regions involved in the evaluation and interpretation of the sensory input.

Information flow in the nervous system

1993 ◽  
Vol 1 (1) ◽  
pp. 31-39
Author(s):  
Arnold Burgen
Keyword(s):  
Information Flow ◽  
Information Transfer ◽  
Sensory Information ◽  
Nerve Fibres ◽  
Ionic Transfer ◽  
Electrical Pulses ◽  
Specific Receptors ◽  
Stored Information ◽  
High Level ◽  
Memory And Recall

Information is carried along nerve fibres by electrical pulses generated by ionic transfer; it is digitally coded. Information transfer between nerve cells depends on the release of a chemical transmitter which acts on specific receptors on the second neurone. This is a non-digital, analogue process which is highly non-linear. It involves the summation of inputs from highly divergent sources. In sensory systems such as vision, extensive compression, feature extraction and other high-level processing occur before presentation to the cerebral cortex, where a massive expansion in distribution of information occurs. Huge numbers of neurones are involved in the central presentation of even simple sensory information. This is because the neural events are relatively slow, so that a massive parallel information flow and processing occurs. Learning and memory involve changes in synaptic efficiency and the development of new stable connective patterns. Memory and recall must involve a comparison of contemporary events with stored information, but cannot involve a one-on-one comparison because it can deal with extensive transformation of sensory information.

scholarly journals Predictive coding over the lifespan: Increased reliance on perceptual priors in older adults – a magnetoencephalography and dynamic causal modelling study

2017 ◽  
Author(s):  
Jason S. Chan ◽  
Michael Wibral ◽  
Patricia Wollstadt ◽  
Cerisa Stawowsky ◽  
Mareike Brandl ◽  
...  
Keyword(s):  
Older Adults ◽  
Life Experience ◽  
Predictive Coding ◽  
Sensory Information ◽  
Younger Adults ◽  
Effective Strategies ◽  
Adult Participants ◽  
Illusory Percept ◽  
The Cost ◽  
Band Activity

AbstractAging is accompanied by unisensory decline; but to compensate for this, two complementary strategies are potentially relied upon increasingly: first, older adults integrate more information from different sensory organs. Second, according to predictive coding (PC) we form ‘templates’ (internal models or ‘priors’) of the environment through our experiences. It is through increased life experience that older adults may rely more on these templates compared to younger adults. Multisensory integration and predictive coding would be effective strategies for the perception of near-threshold stimuli, but they come at the cost of integrating irrelevant information. Their role can be studied in multisensory illusions because these require the integration of different sensory information, as well as an internal model of the world that can take precedence over sensory input. Here, we elicited a classic multisensory illusion, the sound-induced flash illusion, in younger (mean: 27 yrs) and older (mean: 67 yrs) adult participants while recording the magnetoencephalogram. Older adults perceived more illusions than younger adults. Older adults had increased pre-stimulus beta(β)-band activity compared to younger adults as predicted by microcircuit theories of predictive coding, which suggest priors and predictions are linked to β-band activity. In line with our hypothesis, transfer entropy analysis and dynamic causal models of pre-stimulus MEG data revealed a stronger illusion-related modulation of cross-modal connectivity from auditory to visual cortices in older compared to younger adults. We interpret this as the neural correlate of increased reliance on a cross-modal predictive template in older adults that is leading to the illusory percept.

scholarly journals Predictive Coding Over the Lifespan: Increased Reliance on Perceptual Priors in Older Adults—A Magnetoencephalography and Dynamic Causal Modeling Study

2021 ◽  
Vol 13 ◽  
Author(s):  
Jason S. Chan ◽  
Michael Wibral ◽  
Cerisa Stawowsky ◽  
Mareike Brandl ◽  
Saskia Helbling ◽  
...  
Keyword(s):  
Older Adults ◽  
Life Experience ◽  
Predictive Coding ◽  
Sensory Information ◽  
Causal Modeling ◽  
Beta Band ◽  
Dynamic Causal Modeling ◽  
Younger Adults ◽  
Illusory Percept ◽  
Band Activity

Aging is accompanied by unisensory decline. To compensate for this, two complementary strategies are potentially relied upon increasingly: first, older adults integrate more information from different sensory organs. Second, according to the predictive coding (PC) model, we form “templates” (internal models or “priors”) of the environment through our experiences. It is through increased life experience that older adults may rely more on these templates compared to younger adults. Multisensory integration and predictive coding would be effective strategies for the perception of near-threshold stimuli, which may however come at the cost of integrating irrelevant information. Both strategies can be studied in multisensory illusions because these require the integration of different sensory information, as well as an internal model of the world that can take precedence over sensory input. Here, we elicited a classic multisensory illusion, the sound-induced flash illusion, in younger (mean: 27 years, N = 25) and older (mean: 67 years, N = 28) adult participants while recording the magnetoencephalogram. Older adults perceived more illusions than younger adults. Older adults had increased pre-stimulus beta-band activity compared to younger adults as predicted by microcircuit theories of predictive coding, which suggest priors and predictions are linked to beta-band activity. Transfer entropy analysis and dynamic causal modeling of pre-stimulus magnetoencephalography data revealed a stronger illusion-related modulation of cross-modal connectivity from auditory to visual cortices in older compared to younger adults. We interpret this as the neural correlate of increased reliance on a cross-modal predictive template in older adults leading to the illusory percept.

scholarly journals Deep Gated Hebbian Predictive Coding Accounts for Emergence of Complex Neural Response Properties Along the Visual Cortical Hierarchy

2021 ◽  
Vol 15 ◽  
Author(s):  
Shirin Dora ◽  
Sander M. Bohte ◽  
Cyriel M. A. Pennartz
Keyword(s):  
Network Architecture ◽  
Hebbian Learning ◽  
Predictive Coding ◽  
Learning Rule ◽  
Neuronal Populations ◽  
Hebbian Learning Rule ◽  
Cortical Hierarchy ◽  
Latent Representations ◽  
High Level ◽  
Visual Cortical

Predictive coding provides a computational paradigm for modeling perceptual processing as the construction of representations accounting for causes of sensory inputs. Here, we developed a scalable, deep network architecture for predictive coding that is trained using a gated Hebbian learning rule and mimics the feedforward and feedback connectivity of the cortex. After training on image datasets, the models formed latent representations in higher areas that allowed reconstruction of the original images. We analyzed low- and high-level properties such as orientation selectivity, object selectivity and sparseness of neuronal populations in the model. As reported experimentally, image selectivity increased systematically across ascending areas in the model hierarchy. Depending on the strength of regularization factors, sparseness also increased from lower to higher areas. The results suggest a rationale as to why experimental results on sparseness across the cortical hierarchy have been inconsistent. Finally, representations for different object classes became more distinguishable from lower to higher areas. Thus, deep neural networks trained using a gated Hebbian formulation of predictive coding can reproduce several properties associated with neuronal responses along the visual cortical hierarchy.

scholarly journals The role of meaning in visual working memory: Real-world objects, but not simple features, benefit from deeper processing

2020 ◽  
Author(s):  
Timothy F. Brady ◽  
Viola S. Störmer
Keyword(s):  
Working Memory ◽  
Visual Working Memory ◽  
Real World ◽  
Visual Information ◽  
Working Memory Capacity ◽  
Depth Processing ◽  
Single Feature ◽  
High Level ◽  
Simple Features ◽  
Meaningful Stimuli

Visual working memory is a capacity-limited cognitive system used to actively store and manipulate visual information. Visual working memory capacity is not fixed, but varies by stimulus type: stimuli that are more meaningful are better remembered. In the current work, we investigate what conditions lead to the strongest benefits for meaningful stimuli. We propose that in some situations, participants may be prone to try to encode the entire display holistically (i.e., in a quick ‘snapshot’), encouraging participants to treat objects simply as meaningless colored ‘blobs’, rather than processing them individually and in a high-level way, which could reduce benefits for meaningful stimuli. In a series of experiments we directly test whether real-world objects, colors, perceptually-matched less-meaningful objects, and fully scrambled objects benefit from deeper processing. We systematically vary the presentation format of stimuli at encoding to be either simultaneous — encouraging a parallel, ‘take-a-quick-snapshot’ strategy — or present the stimuli sequentially, promoting a serial, each-item-at-once strategy. We find large advantages for meaningful objects in all conditions, but find that real-world objects — and to a lesser degree lightly scrambled, still meaningful versions of the objects — benefit from the sequential encoding and thus deeper, focused-on-individual-items processing, while colors do not. Our results suggest single feature objects may be an outlier in their affordance of parallel, quick processing, and that in more realistic memory situations, visual working memory likely relies upon representations resulting from in-depth processing of objects (e.g., in higher-level visual areas) rather than solely being represented in terms of their low-level features.

scholarly journals Deficits in Prediction Ability Trigger Asymmetries in Behavior and Internal Representation

2020 ◽  
Vol 11 ◽  
Author(s):  
Anja Philippsen ◽  
Yukie Nagai
Keyword(s):  
Developmental Disorders ◽  
Computational Models ◽  
Predictive Coding ◽  
Sensory Information ◽  
Internal Representation ◽  
Human Perception ◽  
Underlying Mechanism ◽  
Autism Spectrum ◽  
Prediction Ability ◽  
And Behavior

Predictive coding is an emerging theoretical framework for explaining human perception and behavior. The proposed underlying mechanism is that signals encoding sensory information are integrated with signals representing the brain's prior prediction. Imbalance or aberrant precision of the two signals has been suggested as a potential cause for developmental disorders. Computational models may help to understand how such aberrant tendencies in prediction affect development and behavior. In this study, we used a computational approach to test the hypothesis that parametric modifications of prediction ability generate a spectrum of network representations that might reflect the spectrum from typical development to potential disorders. Specifically, we trained recurrent neural networks to draw simple figure trajectories, and found that altering reliance on sensory and prior signals during learning affected the networks' performance and the emergent internal representation. Specifically, both overly strong or weak reliance on predictions impaired network representations, but drawing performance did not always reflect this impairment. Thus, aberrant predictive coding causes asymmetries in behavioral output and internal representations. We discuss the findings in the context of autism spectrum disorder, where we hypothesize that too weak or too strong a reliance on predictions may be the cause of the large diversity of symptoms associated with this disorder.

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