Multistable Perception and the Role of the Frontoparietal Cortex in Perceptual Inference

2018 ◽  
Vol 69 (1) ◽  
pp. 77-103 ◽  
Author(s):  
Jan Brascamp ◽  
Philipp Sterzer ◽  
Randolph Blake ◽  
Tomas Knapen
Keyword(s):  
Perceptual Inference ◽  
Multistable Perception ◽  
Frontoparietal Cortex

scholarly journals Concurrent neuroimaging and neurostimulation reveals a causal role for dlPFC in coding of task-relevant information

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Jade B. Jackson ◽  
Eva Feredoes ◽  
Anina N. Rich ◽  
Michael Lindner ◽  
Alexandra Woolgar
Keyword(s):  
Magnetic Stimulation ◽  
Dorsolateral Prefrontal Cortex ◽  
Relevant Information ◽  
Irrelevant Information ◽  
Visual Object ◽  
Information Coding ◽  
Frontoparietal Cortex ◽  
Dorsolateral Prefrontal ◽  
The Impact

AbstractDorsolateral prefrontal cortex (dlPFC) is proposed to drive brain-wide focus by biasing processing in favour of task-relevant information. A longstanding debate concerns whether this is achieved through enhancing processing of relevant information and/or by inhibiting irrelevant information. To address this, we applied transcranial magnetic stimulation (TMS) during fMRI, and tested for causal changes in information coding. Participants attended to one feature, whilst ignoring another feature, of a visual object. If dlPFC is necessary for facilitation, disruptive TMS should decrease coding of attended features. Conversely, if dlPFC is crucial for inhibition, TMS should increase coding of ignored features. Here, we show that TMS decreases coding of relevant information across frontoparietal cortex, and the impact is significantly stronger than any effect on irrelevant information, which is not statistically detectable. This provides causal evidence for a specific role of dlPFC in enhancing task-relevant representations and demonstrates the cognitive-neural insights possible with concurrent TMS-fMRI-MVPA.

scholarly journals Using AI Methods to Evaluate a Minimal Model for Perception

2019 ◽  
Vol 2 (1) ◽  
pp. 503-524 ◽  
Author(s):  
Robert Prentner ◽  
Chris Fields
Keyword(s):  
Conceptual Understanding ◽  
Single Agent ◽  
Psychological Problem ◽  
Machine Learning Techniques ◽  
Distributed Network ◽  
Perceptual Inference ◽  
Interacting Agents ◽  
Learning Techniques ◽  
The Relationship

AbstractThe relationship between philosophy and research on artificial intelligence (AI) has been difficult since its beginning, with mutual misunderstanding and sometimes even hostility. By contrast, we show how an approach informed by both philosophy and AI can be productive. After reviewing some popular frameworks for computation and learning, we apply the AI methodology of “build it and see” to tackle the philosophical and psychological problem of characterizing perception as distinct from sensation. Our model comprises a network of very simple, but interacting agents which have binary experiences of the “yes/no”-type and communicate their experiences with each other. When does such a network refer to a single agent instead of a distributed network of entities? We apply machine learning techniques to address the following related questions: i) how can the model explain stability of compound entities, and ii) how could the model implement a single task such as perceptual inference? We thereby find consistency with previous work on “interface” strategies from perception research.While this reflects some necessary conditions for the ascription of agency, we suggest that it is not sufficient. Here, AI research, if it is intended to contribute to conceptual understanding, would benefit from issues previously raised by philosophy. We thus conclude the article with a discussion of action-selection, the role of embodiment, and consciousness to make this more explicit. We conjecture that a combination of AI research and philosophy allows general principles of mind and being to emerge from a “quasi-empirical” investigation.

The Intricate Interplay of Spatial Attention and Expectation: a Multisensory Perspective

2020 ◽  
Vol 33 (4-5) ◽  
pp. 383-416 ◽  
Author(s):  
Arianna Zuanazzi ◽  
Uta Noppeney
Keyword(s):  
Spatial Attention ◽  
Multisensory Perception ◽  
Critical Question ◽  
Perceptual Inference ◽  
Attentional Resources ◽  
The Senses ◽  
Almost All ◽  
The Impact ◽  
The Brain

Abstract Attention (i.e., task relevance) and expectation (i.e., signal probability) are two critical top-down mechanisms guiding perceptual inference. Attention prioritizes processing of information that is relevant for observers’ current goals. Prior expectations encode the statistical structure of the environment. Research to date has mostly conflated spatial attention and expectation. Most notably, the Posner cueing paradigm manipulates spatial attention using probabilistic cues that indicate where the subsequent stimulus is likely to be presented. Only recently have studies attempted to dissociate the mechanisms of attention and expectation and characterized their interactive (i.e., synergistic) or additive influences on perception. In this review, we will first discuss methodological challenges that are involved in dissociating the mechanisms of attention and expectation. Second, we will review research that was designed to dissociate attention and expectation in the unisensory domain. Third, we will review the broad field of crossmodal endogenous and exogenous spatial attention that investigates the impact of attention across the senses. This raises the critical question of whether attention relies on amodal or modality-specific mechanisms. Fourth, we will discuss recent studies investigating the role of both spatial attention and expectation in multisensory perception, where the brain constructs a representation of the environment based on multiple sensory inputs. We conclude that spatial attention and expectation are closely intertwined in almost all circumstances of everyday life. Yet, despite their intimate relationship, attention and expectation rely on partly distinct neural mechanisms: while attentional resources are mainly shared across the senses, expectations can be formed in a modality-specific fashion.

scholarly journals Hallucinations and perceptual inference

2005 ◽  
Vol 28 (6) ◽  
pp. 764-766 ◽  
Author(s):  
Karl J. Friston
Keyword(s):  
Attention Deficit ◽  
Bayesian Models ◽  
Subjective Perception ◽  
Hierarchical Bayesian ◽  
Hierarchical Bayesian Models ◽  
Perceptual Inference ◽  
Cholinergic Systems ◽  
Neuronal Mechanisms ◽  
Constructive Models

This commentary takes a closer look at how “constructive models of subjective perception,” referred to by Collerton et al. (sect. 2), might contribute to the Perception and Attention Deficit (PAD) model. It focuses on the neuronal mechanisms that could mediate hallucinations, or false inference – in particular, the role of cholinergic systems in encoding uncertainty in the context of hierarchical Bayesian models of perceptual inference (Friston 2002b; Yu & Dayan 2002).

Susceptibility to the Müller-Lyer Illusion and its Relationship to Differences in Size Constancy

1966 ◽  
Vol 18 (1) ◽  
pp. 63-72 ◽  
Author(s):  
Vernon Hamilton
Keyword(s):  
Individual Differences ◽  
Size Constancy ◽  
Direct Test ◽  
Perceptual Inference ◽  
Lyer Illusion ◽  
Perceptual Style ◽  
Constancy Scaling

The hypothesis that susceptibility to the Müller-Lyer illusion is the result of normal constancy scaling, misapplied, was submitted to direct test. No significant correlations between illusion error and size constancy estimates were obtained. Also invalidated were hypotheses that under-constancy is correlated with non-susceptibility to the illusion, and that over-constancy is correlated with greater illusion error. The results suggest that an approach to the explanation of illusion effects by means of analysing individual differences in size constancy, in intelligence and preferred “perceptual style,” might be fruitful. Some tentative suggestions are made concerning the role of perceptual inference, abstraction and analysing.

scholarly journals Attentional dynamics of efficient codes

2021 ◽  
Author(s):  
Wiktor Młynarski ◽  
Gašper Tkačik
Keyword(s):  
Dynamic Environment ◽  
Population Coding ◽  
Top Down ◽  
Brain Areas ◽  
Perceptual Inference ◽  
Efficient Coding ◽  
Activity Cost ◽  
Sensory Code ◽  
State Of The Environment

Top-down attention is hypothesized to dynamically allocate limited neural resources to task-relevant computations. According to this view, sensory neurons are driven not only by stimuli but also by feedback signals from higher brain areas that adapt the sensory code to the goals of the organism and its belief about the state of the environment. Here we formalize this view by optimizing a model of population coding in the visual cortex for maximally accurate perceptual inference at minimal activity cost. The resulting optimality predictions reproduce measured properties of attentional modulation in the visual system and generate novel hypotheses about the functional role of top-down feedback, response variability, and noise correlations. Our results suggest that a range of seemingly disparate attentional phenomena can be derived from a general theory combining probabilistic inference with efficient coding in a dynamic environment.

scholarly journals Delusions and the Role of Beliefs in Perceptual Inference

2013 ◽  
Vol 33 (34) ◽  
pp. 13701-13712 ◽  
Author(s):  
K. Schmack ◽  
A. Gomez-Carrillo de Castro ◽  
M. Rothkirch ◽  
M. Sekutowicz ◽  
H. Rossler ◽  
...  
Keyword(s):  
Perceptual Inference

scholarly journals The Role of Frontoparietal Cortex across the Functional Stages of Visual Search

2021 ◽  
Vol 33 (1) ◽  
pp. 63-76 ◽  
Author(s):  
Roger W. Remington ◽  
Joyce M. G. Vromen ◽  
Stefanie I. Becker ◽  
Oliver Baumann ◽  
Jason B. Mattingley
Keyword(s):  
Visual Search ◽  
Target Selection ◽  
National Academy Of Sciences ◽  
Stimulus Response ◽  
Cognitive Operations ◽  
Frontoparietal Cortex ◽  
Intelligent Behavior ◽  
Academy Of Sciences ◽  
Selection Stage

Areas in frontoparietal cortex have been shown to be active in a range of cognitive tasks and have been proposed to play a key role in goal-driven activities (Dosenbach, N. U. F., Fair, D. A., Miezin, F. M., Cohen, A. L., Wenger, K. K., Dosenbach, R. A. T., et al. Distinct brain networks for adaptive and stable task control in humans. Proceedings of the National Academy of Sciences, U.S.A., 104, 11073–11078, 2007; Duncan, J. The multiple-demand (MD) system of the primate brain: Mental programs for intelligent behavior. Trends in Cognitive Sciences, 14, 172–179, 2010). Here, we examine the role this frontoparietal system plays in visual search. Visual search, like many complex tasks, consists of a sequence of operations: target selection, stimulus–response (SR) mapping, and response execution. We independently manipulated the difficulty of target selection and SR mapping in a novel visual search task that involved identical stimulus displays. Enhanced activity was observed in areas of frontal and parietal cortex during both difficult target selection and SR mapping. In addition, anterior insula and ACC showed preferential representation of SR-stage information, whereas the medial frontal gyrus, precuneus, and inferior parietal sulcus showed preferential representation of target selection-stage information. A connectivity analysis revealed dissociable neural circuits underlying visual search. We hypothesize that these circuits regulate distinct mental operations associated with the allocation of spatial attention, stimulus decisions, shifts of task set from selection to SR mapping, and SR mapping. Taken together, the results show frontoparietal involvement in all stages of visual search and a specialization with respect to cognitive operations.

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