Language Of Thought Research Articles

Unravelling the Cognitive Tapestry: An Exploration of the Interplay between Language and Thought

Language is the primary means through which people convey their thoughts, ideas, emotions, and intentions to others. Effective communication facilitates social interaction, collaboration, and the exchange of information across diverse contexts. It serves as a vehicle for preserving and transmitting cultural heritage from one generation to the next, fostering a sense of belonging and identity among speakers. Language is fundamental in education because it is how knowledge is obtained, shared, and assessed. Input, practice, feedback, and cultural immersion are all components of the dynamic and multidimensional process of language learning, which promotes cognitive growth, linguistic competency, and problem-solving abilities. Delving into the intricate workings of the human mind is a means of unraveling the Cognitive Tapestry. The very language we use influences the way we understand our environment and perceive the ultimate reality we live in. Language and thought are fundamental aspects of cognitive development in humans, each contributing to their ability to communicate, understand others, and navigate the world around them. This paper focuses on the psycholinguistic elements, language, and human thought and the former’s inevitable influence on the latter, as a cognitive process with regard to Linguistic relativity hypothesis. Further, this paper provides insights on the close relationship between language and the mental language in thought production using Language of Thought Hypothesis (LOTH).

A category theory perspective on the Language of Thought: LoT is universal.

The Language of Thought (LoT) hypothesis proposes that some collections of mental states and processes are symbol systems to explain language-like systematic properties of thought. Recent proponents of this hypothesis point to additional LoT-like properties in non-linguistic domains to claim that LoT remains the "best game in town" in terms of explanatory coverage. Nonetheless, LoT assumes but does not explain why/how symbolic representations connect to other (non-symbolic) formats. The perspective presented here is supposed to bridge this gap as a duality in a category theoretical sense: (perceptual) data are projected onto a base (conceptual) space in one direction, and in the opposite direction, these data are referenced by that space. Accordingly, perception is dual to conception. These constructions follow from a universal mapping principle affording an explanation for why/how symbolic and non-symbolic formats are connected: as the "best" possible transformation between the two forms- so the slogan, LoT is universal. This view also sheds some light on the apparent pervasiveness of logic-like capacities across age-groups and species, and these constructions constitute special types of categories called toposes (topoi), and every topos has an interpretation in first-order logic.

The Boolean Language of Thought is recoverable from learning data

According to the Language of Thought Hypothesis (LoTH), an influential account in philosophy and cognitive science, human cognition is underlain by symbolic reasoning in a formal language. In this account, concepts are expressions in a Language of Thought, deduction is syntactic manipulation in this language, and learning is an inference of expressions in this language from data. This picture raises the question of what LoT humans have, and how to infer it from behavior. In this paper, we pave the way towards answering this question, by approaching a more fundamental question: to what extent is it possible in principle to recover the human LoT from experimental data? To answer this question, we focus on the fragment of LoT that is concerned with representing Boolean categories and simulate the recovery of the Boolean LoT from category learning experiments. Our findings show that in principle the vast majority of Boolean LoTs can be accurately recovered from experimental data. However, we find that this crucially depends on the employed experimental design. Moreover, we find evidence that LoTs with fewer operators can be recovered from category learning data faster.

Natralization without associationist reduction: a brief rebuttal to Yoshimi

AbstractYoshimi has attempted to defuse my argument concerning the identification of network abstraction with empiricist abstraction - thus entailing psychologism - by claiming that the argument does not generalize from the example of simple feed-forward networks. I show that such details of networks are logically irrelevant to the nature of the abstractive process they employ. This is ultimately because deep artificial neural networks (ANNs) and dynamical systems theory applied to the mind (DST) are both associationisms - that is, empiricist theories that derive the principles of thought from the causal history of the organism/system. On this basis, I put forward a new aspect of the old argument by noting that ANNs & DST are the causal bases of the phenomena of passive synthesis, whereas the language of thought hypothesis (LOT) and the symbolic computational theory of mind (CTM) are the causal bases of the phenomena of active synthesis. If the phenomena of active synthesis are not distinct in kind from and are thus reducible to those of passive synthesis, psychologism results. Yoshimi’s program, insofar as it denies this fundamental phenomenological distinction, is revealed to be the true anti-pluralist program, by essentially denying the causal efficacy of the mechanistic foundations of active synthesis by referring phenomenology exclusively to associationism for its causal foundation.

Language-of-thought hypothesis: Wrong, but sometimes useful?

Quilty-Dunn et al. maintain that language-of-thought hypothesis (LoTH) is the best game in town. We counter that LoTH is merely one source of models - always wrong, sometimes useful. Their reasons for liking LoTH are compatible with the view that LoTH provides a sometimes pragmatically useful level of abstraction over processes and mechanisms that fail to fully live up to LoT requirements.

The computational and the representational language-of-thought hypotheses.

There are two versions of the language-of-thought hypothesis (LOT): Representational LOT (roughly, structured representation), introduced by Ockham, and computational LOT (roughly, symbolic computation) introduced by Fodor. Like many others, I oppose the latter but not the former. Quilty-Dunn et al. defend representational LOT, but they do not defend the strong computational LOT thesis central to the classical-connectionist debate.

A language of episodic thought?

We propose that episodic thought (i.e., episodic memory and imagination) is a domain where the language-of-thought hypothesis (LoTH) could be fruitfully applied. On the one hand, LoTH could explain the structure of what is encoded into and retrieved from long-term memory. On the other, LoTH can help make sense of how episodic contents come to play such a large variety of different cognitive roles after they have been retrieved.

Developmental and multiple languages-of-thought.

We agree with the target article that assuming language-of-thought (LoT) is useful for the development of cognitive and developmental theories. We note that the target article is weak in its assumptions about development of LoT and possible existence of multiple LoTs. In response to these weaknesses, we outline several developmental principles for LoT development, showing how a developmental theory of LoT springs from probabilistic LoT. We suggest a system 1.5 of reasoning allowing interchange between Bayesian and logical rules as it fits purposes or domain.

Compositionality in visual perception.

Quilty-Dunn et al.'s wide-ranging defense of the Language of Thought Hypothesis (LoTH) argues that vision traffics in abstract, structured representational formats. We agree: Vision, like language, is compositional - just as words compose into phrases, many visual representations contain discrete constituents that combine in systematic ways. Here, we amass evidence extending this proposal, and explore its implications for how vision interfaces with the rest of the mind.

Is language-of-thought the best game in the town we live?

There are towns in which language-of-thought (LoT) is the best game. But do we live in one? I go through three properties that characterize the LoT hypothesis: Discrete constituents, role-filler independence, and logical operators, and argue that in each case predictions from the LoT hypothesis are a poor fit to actual human cognition. As a hypothesis of what human cognition ought to be like, LoT departs from empirical reality.

Perception is iconic, perceptual working memory is discursive.

The evidence that the target article cites for language-of-thought (LoT) structure in perceptual object representations concerns perceptual working memory, not perception. Perception is iconic, not structured like an LoT. Perceptual working memory representations contain the remnants of iconic perceptual representations, often recoded, in a discursive envelope.

The language-of-thought as a working hypothesis for developmental cognitive science.

A science of prelinguistic infant cognition must take seriously the language-of-thought (LoT) hypothesis. I show how the LoT framework enables us to identify the representational and computational capacities of infant minds and the developmental factors that act on these capacities, and explain how Quilty-Dunn et al.'s take on LoT has important upshots for developmental theory-building.

Linguistic meanings in mind.

The target article focuses on evidence from nonlinguistic faculties to defend the claim that cognition generally traffics in language-of-thought (LoT)-type representations. This focus creates needed space to discuss the mounting accumulation of nonclassical evidence for LoT, but it also misses relevant work in linguistics that directly offers a perspective on specific hypotheses about candidate LoT representations.

The language of tactile thought.

The target article argues that language-of-thought hypothesis (LoTH) is applicable to various domains, including perception. However, it focusses exclusively on the visual case, which is limited in this regard. I argue for two ideas in this commentary: first, their case can be extended to other modalities such as touch; and second, the status of those six criteria needs to be further clarified.

Natural logic and baby LoTH.

Language-of-thought hypothesis (LoTH) is having a profound impact on cognition studies. However, much remains unknown about its basic primitives and generative operations. Infant studies are fundamental, but methodologically very challenging. By distilling potential primitives from work in natural-language semantics, an approach beyond the corset of standard formal logic may be undertaken. Still, the road ahead is challenging and long.

Animal thought exceeds language-of-thought.

Quilty-Dunn et al. claim that all complex infant and animal reasoning implicate language-of-thought hypothesis (LOTH)-like structures. We agree with the authors that the mental life of animals can be explained in representationalist terms, but we disagree with their idea that the complexity of mental representations is best explained by appealing to abstract concepts, and instead, we explain that it doesn't need to.

Toward biologically plausible artificial vision.

Quilty-Dunn et al. argue that deep convolutional neural networks (DCNNs) optimized for image classification exemplify structural disanalogies to human vision. A different kind of artificial vision - found in reinforcement-learning agents navigating artificial three-dimensional environments - can be expected to be more human-like. Recent work suggests that language-like representations substantially improves these agents' performance, lending some indirect support to the language-of-thought hypothesis (LoTH).

The reemergence of the language-of-thought hypothesis: Consequences for the development of the logic of thought.

Quilty-Dunn et al. defended the reemergence of language-of-thought hypothesis (LoTH). My commentary builds up implications for the study of the development of our logical capacities. Empirical support for logically augmented LoT systems calls for the investigation of their logical primitives and developmental origin. Furthermore, Quilty-Dunn et al.'s characterization of LoT helps the quest for the foundation of logic by dissociating logical cognition from natural language.

Never not the best: LoT and the explanation of person-level psychology.

As Quilty-Dunn et al. observe, the language-of-thought hypothesis (LoTH) has fallen out of favor in philosophy. I will support the arguments made for its rehabilitation by Quilty-Dunn et al. by reviewing old, but still potent arguments for LoTH, and briefly criticizing recent proposed alternatives to LoT, such as Frances Egan's deflationism and Eric Schwitzgebel's dispositionalism, revealing inadequacies in such antirepresentational, antisyntactic theories.

Is core knowledge in the format of LOT?

Object individuation provides a test case for the claim that infants already have a prelinguistic language-of-thought (LOT). By 12 months, infants represent several sortal-kinds: Object, agent, animate, and perhaps artifact. Infants have also encountered many words for object kinds, animals, people, and artifacts, therefore it remains a viable hypothesis that language learning may play a causal role in the acquisition of sortal-kinds, contra Quilty-Dunn et al.