The Computational Theory of Mind

Опубликована: Ноя. 13, 2023

The Computational Theory of Mind says that the mind is a computing system. It has long history going back to idea thought kind computation. Its modern incarnation relies on analogies with contemporary technology and use computational models. comes in many versions, some more plausible than others. This Element supports theory primarily by its contribution solving mind-body problem, ability explain mental phenomena, success modelling artificial intelligence. To be turned into an adequate theory, it needs made compatible tractability cognition, situatedness dynamical aspects mind, way brain works, intentionality, consciousness.

Язык: Английский

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Seeing social interactions

Trends in Cognitive Sciences, Год журнала: 2023, Номер 27(12), С. 1165 - 1179

Опубликована: Окт. 5, 2023

Seeing the interactions between other people is a critical part of our everyday visual experience, but recognizing social others often considered outside scope vision and grouped with higher-level cognition like theory mind. Recent work, however, has revealed that recognition efficient automatic, well modeled by bottom-up computational algorithms, occurs in visually-selective regions brain. We review recent evidence from these three methodologies (behavioral, computational, neural) converge to suggest core interaction perception visual. propose framework for how this process carried out brain offer directions future interdisciplinary investigations perception.

Язык: Английский

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Visual Representations: Insights from Neural Decoding

Annual Review of Vision Science, Год журнала: 2023, Номер 9(1), С. 313 - 335

Опубликована: Март 8, 2023

Patterns of brain activity contain meaningful information about the perceived world. Recent decades have welcomed a new era in neural analyses, with computational techniques from machine learning applied to data decode represented brain. In this article, we review how decoding approaches advanced our understanding visual representations and discuss efforts characterize both complexity behavioral relevance these representations. We outline current consensus regarding spatiotemporal structure recent findings that suggest are at once robust perturbations, yet sensitive different mental states. Beyond physical world, work has shone light on instantiates internally generated states, for example, during imagery prediction. Going forward, remarkable potential assess functional human behavior, reveal change across development aging, uncover their presentation various disorders.

Язык: Английский

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Neural representation in active inference: Using generative models to interact with—and understand—the lived world

Annals of the New York Academy of Sciences, Год журнала: 2024, Номер 1534(1), С. 45 - 68

Опубликована: Март 25, 2024

Abstract This paper considers neural representation through the lens of active inference, a normative framework for understanding brain function. It delves into how living organisms employ generative models to minimize discrepancy between predictions and observations (as scored with variational free energy). The ensuing analysis suggests that learns navigate world adaptively, not (or solely) understand it. Different may possess an array models, spanning from those support action‐perception cycles underwrite planning imagination; namely, explicit entail variables predicting concurrent sensations, like objects, faces, or people—to action‐oriented predict action outcomes. then elucidates belief dynamics might link implications different types agent's cognitive capabilities in relation its ecological niche. concludes open questions regarding evolution development advanced abilities—and gradual transition pragmatic detached representations. on offer foregrounds diverse roles play processes representation.

Язык: Английский

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Connectivity analyses for task-based fMRI

Physics of Life Reviews, Год журнала: 2024, Номер 49, С. 139 - 156

Опубликована: Апрель 30, 2024

Functional connectivity (FC) is conventionally defined by measuring the similarity between brain signals from two regions. The technique has become widely adopted in analysis of functional magnetic resonance imaging (fMRI) data, where it provided cognitive neuroscientists with abundant information on how regions interact to support complex cognition. However, past decade notion "connectivity" expanded both complexity and heterogeneity its application neuroscience, resulting greater difficulty interpretation, replication, cross-study comparisons. In this paper, we begin canonical notions then introduce recent methodological developments that either estimate some alternative form or extend analytical framework, hope bringing better clarity for neuroscience researchers.

Язык: Английский

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Theory Is All You Need: AI, Human Cognition, and Decision Making

SSRN Electronic Journal, Год журнала: 2024, Номер unknown

Опубликована: Янв. 1, 2024

Artificial intelligence (AI) now matches or outperforms human in an astonishing array of games, tests, and other cognitive tasks that involve high-level reasoning thinking. Many scholars argue that—due to bias bounded rationality—humans should (or will soon) be replaced by AI situations involving cognition strategic decision making. We disagree. In this paper we first trace the historical origins idea artificial as a form computation information processing. highlight problems with analogy between computers minds input-output devices, using large language models example. Human cognition—in important instances—is better conceptualized theorizing rather than data processing, prediction, even Bayesian updating. Our argument, when it comes cognition, is AI's data-based prediction different from theory-based causal logic. introduce belief-data (a)symmetries difference use "heavier-than-air flight" example our arguments. Theories provide mechanism for identifying new evidence, way "intervening" world, experimenting, problem solving. conclude discussion implications arguments making, including role human-AI hybrids might play process.

Язык: Английский

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The concept of representation in the brain sciences: The current status and ways forward

Mind & Language, Год журнала: 2025, Номер unknown

Опубликована: Фев. 26, 2025

This article outlines the motivations and main findings of Favela Machery's “Investigating concept representation in neural psychological sciences”, discusses what to do with brain sciences moving forward.

Язык: Английский

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Investigating the concept of representation in the neural and psychological sciences

Frontiers in Psychology, Год журнала: 2023, Номер 14

Опубликована: Июнь 7, 2023

The concept of representation is commonly treated as indispensable to research on brains, behavior, and cognition. Nevertheless, systematic evidence about the ways applied remains scarce. We present results an experiment aimed at elucidating what researchers mean by "representation." Participants were international group psychologists, neuroscientists, philosophers (N = 736). Applying elicitation methodology, participants responded a survey with experimental scenarios invoking applications "representation" five other describing how brain responds stimuli. While we find little disciplinary variation in application expressions (e.g., "about" "carry information"), suggest that exhibit uncertainty sorts activity involve representations or not; they also prefer non-representational, causal characterizations brain's response Potential consequences these findings are explored, such reforming eliminating from use.

Язык: Английский

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Distinct ventral stream and prefrontal cortex representational dynamics during sustained conscious visual perception

Cell Reports, Год журнала: 2023, Номер 42(7), С. 112752 - 112752

Опубликована: Июль 1, 2023

Instances of sustained stationary sensory input are ubiquitous. However, previous work focused almost exclusively on transient onset responses. This presents a critical challenge for neural theories consciousness, which should account the full temporal extent experience. To address this question, we use intracranial recordings from ten human patients with epilepsy to view diverse images multiple durations. We reveal that, in regions, despite dramatic changes activation magnitude, distributed representation categories and exemplars remains stable. In contrast, frontoparietal find content at stimulus onset. Our results highlight connection between anatomical correlates perception is sustained, it may rely representations discrete, centered perceptual updating, representations.

Язык: Английский

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Theory Is All You Need: AI, Human Cognition, and Causal Reasoning

Strategy Science, Год журнала: 2024, Номер unknown

Опубликована: Дек. 3, 2024

Scholars argue that artificial intelligence (AI) can generate genuine novelty and new knowledge and, in turn, AI computational models of cognition will replace human decision making under uncertainty. We disagree. AI’s data-based prediction is different from theory-based causal logic reasoning. highlight problems with the decades-old analogy between computers minds as input–output devices, using large language an example. Human better conceptualized a form reasoning rather than emphasis on information processing prediction. uses probability-based approach to largely backward looking imitative, whereas forward-looking capable generating novelty. introduce idea data–belief asymmetries difference cognition, example heavier-than-air flight illustrate our arguments. Theory-based provides cognitive mechanism for humans intervene world engage directed experimentation data. Throughout article, we discuss implications argument understanding origins novelty, knowledge,

Язык: Английский

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