Priors and Prejudice: How prior knowledge shapes intergroup perception

2021 ◽  
Author(s):  
Hugh McGovern ◽  
Marte Otten
Keyword(s):  
Social Psychology ◽  
Prior Knowledge ◽  
Cognitive Processes ◽  
Social Neuroscience ◽  
Intergroup Bias ◽  
Predictive Processing ◽  
Future Research ◽  
Intergroup Perception ◽  
The Brain ◽  
Processing Framework

Bayesian processing has become a popular framework by which to understand cognitive processes. However, relatively little has been done to understand how Bayesian processing in the brain can be applied to understanding intergroup cognition. We assess how categorization and evaluation processes unfold based on priors about the ethnic outgroup being perceived. We then consider how the precision of prior knowledge about groups differentially influence perception depending on how the information about that group was learned affects the way in which it is recalled. Finally, we evaluate the mechanisms of how humans learn information about other ethnic groups and assess how the method of learning influences future intergroup perception. We suggest that a predictive processing framework for assessing prejudice could help accounting for seemingly disparate findings on intergroup bias from social neuroscience, social psychology, and evolutionary psychology. Such an integration has important implications for future research on prejudice at the interpersonal, intergroup, and societal levels.

Machine Learning and Cognitive Algorithms for Engineering Applications

2013 ◽  
Vol 7 (4) ◽  
pp. 64-82 ◽  
Author(s):  
Leonid Perlovsky ◽  
Gary Kuvich
Keyword(s):  
Fuzzy Logic ◽  
Cognitive Processes ◽  
Future Research ◽  
Abstract Concepts ◽  
Cognitive Mechanisms ◽  
Research Directions ◽  
Semiotic Approach ◽  
Future Research Directions ◽  
The Brain ◽  
Universal Representation

Mind is based on intelligent cognitive processes, which are not limited by language and logic only. The thought is a set of informational processes in the brain, and such processes have the same rationale as any other systematic informational processes. Their specifics are determined by the ways of how brain stores, structures, and process this information. Systematic approach allows representing them in a diagrammatic form that can be formalized. Semiotic approach allows for the universal representation of such diagrams. In that approach, logic is a way of synthesis of such structures, which is a small but clearly visible top of the iceberg. The most efforts were traditionally put into logics without paying much attention to the rest of the mechanisms that make the entire thought system working autonomously. Dynamic fuzzy logic is reviewed and its connections with semiotics are established. Dynamic fuzzy logic extends fuzzy logic in the direction of logic-processes, which include processes of fuzzification and defuzzification as parts of logic. The paper reviews basic cognitive mechanisms, including instinctual drives, emotional and conceptual mechanisms, perception, cognition, language, a model of interaction between language and cognition upon the new semiotic models. The model of interacting cognition and language is organized in an approximate hierarchy of mental representations from sensory percepts at the “bottom” to objects, contexts, situations, abstract concepts-representations, and to the most general representations at the “top” of mental hierarchy. Knowledge Instinct and emotions are driving feedbacks for these representations. Interactions of bottom-up and top-down processes in such hierarchical semiotic representation are essential for modeling cognition. Dynamic fuzzy logic is analyzed as a fundamental mechanism of these processes. Future research directions are discussed.

The Regularity Account of Phenomenal Unity

2018 ◽  
Author(s):  
Wanja Wiese
Keyword(s):  
Conscious Experience ◽  
Predictive Processing ◽  
Formal Description ◽  
Rigorous Formulation ◽  
Formal Concepts ◽  
The Brain ◽  
Processing Framework ◽  
Phenomenal Unity

This chapter presents the regularity account of phenomenal unity (RPU). The basic idea of RPU is that when the brain tracks a regularity that is predictive of different features (or of different objects or events), there will be an experienced connection between those features (or the respective objects or events). We can then say that the regularity connects those features (or objects or events). According to RPU, unity comes in degrees, and in ordinary conscious experience we find a hierarchy of experienced wholes. This chapter provides a preliminary taxonomy of experienced wholes, with many examples. Drawing on formal concepts of the predictive processing framework, a formal description of possible computational underpinnings of experienced wholeness is given. Finally, a rigorous formulation of the mélange model (first proposed in chapter 4) is provided.

scholarly journals Spotlight commentary: REBUS and the anarchic brain

2020 ◽  
Vol 2020 (1) ◽  
Author(s):  
Tehseen Noorani ◽  
Ben Alderson-Day
Keyword(s):  
Contextual Factors ◽  
Mechanisms Of Action ◽  
Unified Model ◽  
Predictive Processing ◽  
Altered States ◽  
The Brain ◽  
Processing Framework

Abstract In ‘REBUS and the Anarchic Brain: Towards a Unified Model of the Brain Action of Psychedelics’, Carhart-Harris and Friston offer an important analysis of what the predictive processing framework has to offer our understanding of psychedelic experiences, providing an invaluable ground for psychedelic psychiatry. While applauding this, we encourage paying greater attention to contextual factors shaping extreme experiences and their sequalae, and suggest that the authors’ comparisons with certain non-psychedelic altered states may overlook more informative parallels that can be drawn elsewhere. Addressing both points will prove fruitful, ultimately, in identifying the mechanisms of action of greatest interest in psychedelic experiences.

COGNITIVE MECHANISMS OF THE MIND

2013 ◽  
Vol 09 (03) ◽  
pp. 301-323 ◽  
Author(s):  
GARY KUVICH ◽  
LEONID PERLOVSKY
Keyword(s):  
Fuzzy Logic ◽  
Cognitive Processes ◽  
Human Mind ◽  
Future Research ◽  
Abstract Concepts ◽  
Cognitive Mechanisms ◽  
Excellent Work ◽  
Future Research Directions ◽  
The Mind ◽  
The Brain

Successes of information and cognitive science brought a growing understanding that mind is based on intelligent cognitive processes, which are not limited by language and logic only. A nice overview can be found in the excellent work of Jeff Hawkins "On Intelligence." This view is that thought is a set of informational processes in the brain, and such processes have the same rationale as any other systematic informational processes. Their specifics are determined by the ways of how brain stores, structures and process this information. Systematic approach allows representing them in a diagrammatic form that can be formalized and programmed. Semiotic approach allows for the universal representation of such diagrams. In our approach, logic is just a way of synthesis of such structures, which is a small but clearly visible top of the iceberg. However, most of the efforts were traditionally put into logics without paying much attention to the rest of the mechanisms that make the entire thought system working autonomously. Dynamic fuzzy logic is reviewed and its connections with semiotics are established. Dynamic fuzzy logic extends fuzzy logic in the direction of logic-processes, which include processes of fuzzification and defuzzification as parts of logic. This extension of fuzzy logic is inspired by processes in the brain-mind. The paper reviews basic cognitive mechanisms, including instinctual drives, emotional and conceptual mechanisms, perception, cognition, language, a model of interaction between language and cognition upon the new semiotic models. The model of interacting cognition and language is organized in an approximate hierarchy of mental representations from sensory percepts at the "bottom" to objects, contexts, situations, abstract concepts-representations, and to the most general representations at the "top" of mental hierarchy. Knowledge instinct and emotions are driving feedbacks for these representations. Interactions of bottom-up and top-down processes in such hierarchical semiotic representation are essential for modeling cognition. Dynamic fuzzy logic is analyzed as a fundamental mechanism of these processes. In this paper we are trying to formalize cognitive processes of the human mind using approaches above, and provide interfaces that could allow for their practical realization in software and hardware. Future research directions are discussed.

scholarly journals The brain, self and society: a social-neuroscience model of predictive processing

2018 ◽  
Vol 14 (3) ◽  
pp. 266-276 ◽  
Author(s):  
Michael P Kelly ◽  
Natasha M. Kriznik ◽  
Ann Louise Kinmonth ◽  
Paul C. Fletcher
Keyword(s):  
Social Neuroscience ◽  
Predictive Processing ◽  
The Brain

Supercharged Apes versus Super-Sized Minds

2019 ◽  
pp. 99-112
Author(s):  
Louise Barrett
Keyword(s):  
Information Processing ◽  
Cognitive Load ◽  
Cognitive Science ◽  
Extended Mind ◽  
Predictive Processing ◽  
Processing Activity ◽  
Evolutionary Continuity ◽  
The Brain ◽  
Processing Framework ◽  
The Way

Clark’s philosophy brings body, brain, and world together again, offering a new conception of both human and nonhuman cognition. This chapter agrees that the predictive processing framework provides our best bet for a species-neutral cognitive science. However, the use of cognitivist, representational language often seems unnecessary, especially when J. J. Gibson introduced a “resonance” metaphor to replace notions of representation, hypothesis, and inference. This chapter is therefore interested to know why Clark resists embracing Gibson, when this seems one of the best ways to embrace evolutionary continuity. The chapter also raises the apparent tension between the predictive processing position and that of the extended mind: Is the brain the principal seat of information-processing activity? Or is it userless tools all the way down? Finally, the chapter raises the issue of epistemic artefacts, and whether these increase or decrease cognitive load.

The Predictive Processing Hypothesis

2018 ◽  
pp. 128-146
Author(s):  
Jakob Hohwy
Keyword(s):  
Cognitive Processing ◽  
Extended Cognition ◽  
Predictive Processing ◽  
Central Concept ◽  
Initial Impression ◽  
4E Cognition ◽  
The Brain ◽  
Perception Action ◽  
Processing Framework

Prediction may be a central concept for understanding perceptual and cognitive processing. Contemporary theoretical neuroscience formalizes the role of prediction in terms of probabilistic inference. Perception, action, attention, and learning may then be unified as aspects of predictive processing in the brain. This chapter first explains the sense in which predictive processing is inferential and representational. Then follows an exploration of how the predictive processing framework relates to a series of considerations in favor of enactive, embedded, embodied, and extended cognition (4E cognition). The initial impression may be that predictive processing is too representational and inferential to fit well to 4E cognition. But, in fact, predictive processing encompasses many phenomena prevalent in 4E approaches, while remaining both inferential and representational.

scholarly journals The Social Neuroscience of Prejudice

2021 ◽  
Vol 72 (1) ◽  
pp. 439-469 ◽  
Author(s):  
David M. Amodio ◽  
Mina Cikara
Keyword(s):  
Social Psychology ◽  
Decision Making ◽  
Self Regulation ◽  
Social Neuroscience ◽  
The Self ◽  
Intergroup Bias ◽  
Societal Issues ◽  
Psychological Theories ◽  
The Social ◽  
Prejudice And Discrimination

The social neuroscience approach to prejudice investigates the psychology of intergroup bias by integrating models and methods of neuroscience with the social psychology of prejudice, stereotyping, and discrimination. Here, we review major contemporary lines of inquiry, including current accounts of group-based categorization; formation and updating of prejudice and stereotypes; effects of prejudice on perception, emotion, and decision making; and the self-regulation of prejudice. In each section, we discuss key social neuroscience findings, consider interpretational challenges and connections with the behavioral literature, and highlight how they advance psychological theories of prejudice. We conclude by discussing the next-generation questions that will continue to guide the social neuroscience approach toward addressing major societal issues of prejudice and discrimination.

scholarly journals How Working Memory and Reinforcement Learning Are Intertwined: A Cognitive, Neural, and Computational Perspective

2021 ◽  
pp. 1-17
Author(s):  
Aspen Yoo ◽  
Anne Collins
Keyword(s):  
Working Memory ◽  
Reinforcement Learning ◽  
Cognitive Processes ◽  
Review Literature ◽  
Human Cognition ◽  
Future Research ◽  
Artificial Agents ◽  
Comprehensive Understanding ◽  
Complex Interactions ◽  
The Brain

Abstract Reinforcement learning and working memory are two core processes of human cognition and are often considered cognitively, neuroscientifically, and algorithmically distinct. Here, we show that the brain networks that support them actually overlap significantly and that they are less distinct cognitive processes than often assumed. We review literature demonstrating the benefits of considering each process to explain properties of the other and highlight recent work investigating their more complex interactions. We discuss how future research in both computational and cognitive sciences can benefit from one another, suggesting that a key missing piece for artificial agents to learn to behave with more human-like efficiency is taking working memory's role in learning seriously. This review highlights the risks of neglecting the interplay between different processes when studying human behavior (in particular when considering individual differences). We emphasize the importance of investigating these dynamics to build a comprehensive understanding of human cognition.

scholarly journals Susceptibility to auditory hallucinations is associated with spontaneous but not directed modulation of top-down expectations for speech.

2021 ◽  
Author(s):  
Ben Alderson-Day ◽  
Jamie A. Moffatt ◽  
Cesar Lima ◽  
Saloni Krishnan ◽  
Charles Fernyhough ◽  
...  
Keyword(s):  
Prior Knowledge ◽  
Sine Wave ◽  
Predictive Processing ◽  
Future Research ◽  
Top Down ◽  
Hearing Voices ◽  
Auditory Verbal Hallucinations ◽  
Speech Stimuli ◽  
Original Language ◽  
Before And After

Auditory verbal hallucinations (AVH) – or hearing voices – occur in clinical and non-clinical populations, but their mechanisms remain unclear. Predictive processing models of psychosis have proposed that hallucinations arise from an over-weighting of prior expectations in perception. It is unknown, however, whether this reflects i) a sensitivity to explicit modulation of prior knowledge, or ii) a pre-existing tendency to spontaneously use such knowledge more in ambiguous contexts. Four experiments were conducted to examine this question in healthy participants listening to ambiguous speech stimuli. In experiments 1 (n = 60) and 2 (n = 60), participants discriminated intelligible and unintelligible sine-wave speech (SWS) before and after exposure to the original language templates (i.e., a modulation of expectation). No relationship was observed between top-down modulation and two common measures of hallucination-proneness. Experiment 3 (n = 99) confirmed this pattern with a different stimulus – sine-vocoded speech (SVS) – that was designed to minimise ceiling effects in discrimination and more closely model previous top-down effects reported in psychosis. In Experiment 4 (n = 135), participants were exposed to SVS without prior knowledge that it contained speech (i.e., naïve listening). AVH-proneness significantly predicted spontaneous pre-exposure identification of speech, but was unrelated to performance on a subsequent discrimination task, post-exposure. Altogether, these findings support a pre-existing tendency to spontaneously draw upon prior knowledge in healthy people prone to AVH, rather than a sensitivity to temporary modulations of expectation. We propose a model of clinical and non-clinical hallucinations, across auditory and visual modalities, with testable predictions for future research.

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