In his highly influential "The Interpretation of Cultures," anthropologist Clifford Geertz argues that the study of culture ought to be "not an experimental science in search of law but an interpretive one in search of meaning." I argue that the two need not be opposed. The best way of making sense of the social scientific practice of looking at meaning is to see interpretivists as looking at typical mental reactions that people in a given culture have to certain acts and (...) artifacts. I argue that scientific theories of the mental—rather than minimalist—theories are needed for this practice to be successful. (shrink)

The ability to reason about how things were made is a pervasive aspect of how humans make sense of physical objects. Such reasoning is useful for a range of everyday tasks, from assembling a piece of furniture to making a sandwich and knitting a sweater. What enables people to reason in this way even about novel objects, and how do people draw upon prior experience with an object to continually refine their understanding of how to create it? To explore these (...) questions, we developed a virtual task environment to investigate how people come up with step‐by‐step procedures for recreating block towers whose composition was not readily apparent, and analyzed how the procedures they used to build them changed across repeated attempts. Specifically, participants (N = 105) viewed 2D silhouettes of eight unique block towers in a virtual environment simulating rigid‐body physics, and aimed to reconstruct each one in less than 60 s. We found that people built each tower more accurately and quickly across repeated attempts, and that this improvement reflected both group‐level convergence upon a tiny fraction of all possible viable procedures, as well as error‐dependent updating across successive attempts by the same individual. Taken together, our study presents a scalable approach to measuring consistency and variation in how people infer solutions to physical assembly problems. (shrink)

The value of accuracy and quantity as memory measures is assessed. It is argued that (1) accuracy does not measure correspondence (monitoring) because it ignores omissions and correct rejections, (2) quantity is confounded with monitoring in recall, and (3) in recognition, if targets and foils are unequal, both measures, even together, still ignore correct rejections.

Evans’ 1968 ANALOGY system was the first computer model of analogy. This paper demonstrates that the structure mapping model of analogy, when combined with high‐level visual processing and qualitative representations, can solve the same kinds of geometric analogy problems as were solved by ANALOGY. Importantly, the bulk of the computations are not particular to the model of this task but are general purpose: We use our existing sketch understanding system, CogSketch, to compute visual structure that is used by our existing (...) analogical matcher, Structure Mapping Engine (SME). We show how SME can be used to facilitate high‐level visual matching, proposing a role for structural alignment in mental rotation. We show how second‐order analogies over differences computed via analogies between pictures provide a more elegant model of the geometric analogy task. We compare our model against human data on a set of problems, showing that the model aligns well with both the answers chosen by people and the reaction times required to choose the answers. (shrink)

Localist models of spreading activation (SA) and models assuming distributed representations offer very different takes on semantic priming, a widely investigated paradigm in word recognition and semantic memory research. In this study, we implemented SA in an attractor neural network model with distributed representations and created a unified framework for the two approaches. Our models assume a synaptic depression mechanism leading to autonomous transitions between encoded memory patterns (latching dynamics), which account for the major characteristics of automatic semantic priming in (...) humans. Using computer simulations, we demonstrated how findings that challenged attractor‐based networks in the past, such as mediated and asymmetric priming, are a natural consequence of our present model’s dynamics. Puzzling results regarding backward priming were also given a straightforward explanation. In addition, the current model addresses some of the differences between semantic and associative relatedness and explains how these differences interact with stimulus onset asynchrony in priming experiments. (shrink)

The novel correspondence metaphor outlined by Koriat & Goldsmith offers important advantages for studying critical issues of memory-accuracy. It also fits well with the current emphasis on the reconstructive nature of memory and on the role of cognitive, metacognitive, and motivational factors in memory performance. These positive features notwithstanding, the storehouse/correspondence framework faces potential perils having to do with its implied linkage to the laboratory/real-life controversy and its proposal of studying correspondence issues in isolation from memory phenomena captured by the (...) storehouse paradigm. (shrink)

Do properties of a word's features influence the order of its acquisition in early word learning? Combining the principles of mutual exclusivity and shape bias, the present work takes a network analysis approach to understanding how feature distinctiveness predicts the order of early word learning. Distance networks were built from nouns with edge lengths computed using various distance measures. Feature distinctiveness was computed as a distance measure, showing how far an object in a network is from other objects based on (...) shared and non‐shared features. Feature distinctiveness predicted order of acquisition across all measures: Words that were further away from other words in the network space were learned earlier. The best distance measures were based only on non‐shared features (object dissimilarity) and did not include shared features (object similarity). This indicates that shared features may play less of a role in early word learning than non‐shared features. In addition, the strongest effects were found for visual form and surface features. Cluster analysis further revealed that this effect is a localized effect in the object feature space, where objects' distances from their cluster centroid were inversely correlated with their age of acquisition. Together, these results suggest a role for feature distinctiveness in early word learning. (shrink)

Our response to the commentators covers four general issues: (1) How useful is our proposed conceptualization of the real-life/laboratory controversy in terms of the contrast between the correspondence and storehouse metaphors? (2) What is the relationship between these two metaphors? (3) What are the unique implications of the correspondence metaphor for memory assessment and theory? (4) What are the nature and role of memory metaphors in memory research? We stress that the correspondence metaphor can be usefully exploited independent of the (...) real-life/laboratory controversy, but that a variety of other metaphors, including the storehouse, should also be utilized in order to more fully capture the myriad facets and functions of memory in everyday life. (shrink)

Jeannerod's target article describes support, through empirical and neurological findings, for the intriguing idea of motor imagery, a form of representation hypothesized to have levels of functional equivalence with motor preparation, while being consciously accessible. Jeannerod suggests that the subjectively accessible content of motor imagery allows it to be distinguished from motor preparation, which is unconscious. Motor imagery is distinguished from visual imagery in terms of content. Motor images are kinesthetic in nature; they are parametrized by variables such as force (...) and time and they are potentially governed by kinematic rules. Jeannerod acknowledges, however, that motor and visual imagery may not easily be separated, because actions take place in a spatial environment. I agree; in fact, I suggest here that visualization may generally be concomitant with, and may even subjectively dominate, motor imagery. (shrink)

Koriat & Goldsmith restrict their definition of memory to “being about some past event,” which causes them to ignore the most common use of memory: everyday visual-motor tasks. New techniques make it possible to study memory in the context of these natural tasks with which memory is so tightly coupled. Memory can be more fully understood in the context of these actions.

A theoretical pillars of vision science in the information-processing tradition is that perception involves unconscious inference. The classic support for this claim is that, since retinal inputs underdetermine their distal causes, visual perception must be the conclusion of a process that starts with premises representing both the sensory input and previous knowledge about the visible world. Focus on this “argument from underdetermination” gives the impression that, if it fails, there is little reason to think that visual processing involves unconscious inference. (...) Here an alternative means of support for this pillar is proposed, based on another foundational challenge for the visual system: recognizing invariant properties of objects in the environment even though anything we encounter is never seen exactly the same way twice. Explaining how the visual system solves this invariance problem requires positing visual processes that exhibit many commonalities with inductive inference. Thus, this novel “argument from invariance” reveals one way in which visual processing clearly involves unconscious inference. (shrink)

Formal theories of mental representation have receded from the importance they had in the early days of cognitive science. I argue that such theories are crucial in any mental domain, not just for their own sake, but to guide experimental inquiry, as well as to integrate the domain into the mind as a whole. To illustrate the criteria of adequacy for theories of mental representation, I compare two theoretical approaches to language: classical generative grammar (Chomsky, 1965, 1981, 1995) and the (...) parallel architecture (Jackendoff, 1997, 2002). The grounds for comparison include (a) the internal coherence of the theory across phonology, syntax, and semantics; (b) the relation of language to other mental faculties; (c) the relationship between grammar and lexicon; (d) relevance to theories of language processing; and (e) the possibility of languages with little or no syntax. (shrink)

Applying machine learning algorithms to automatically infer relationships between concepts from large-scale collections of documents presents a unique opportunity to investigate at scale how human semantic knowledge is organized, how people use it to make fundamental judgments (“How similar are cats and bears?”), and how these judgments depend on the features that describe concepts (e.g., size, furriness). However, efforts to date have exhibited a substantial discrepancy between algorithm predictions and human empirical judgments. Here, we introduce a novel approach to generating (...) embeddings for this purpose motivated by the idea that semantic context plays a critical role in human judgment. We leverage this idea by constraining the topic or domain from which documents used for generating embeddings are drawn (e.g., referring to the natural world vs. transportation apparatus). Specifically, we trained state-of-the-art machine learning algorithms using contextually-constrained text corpora (domain-specific subsets of Wikipedia articles, 50+ million words each) and showed that this procedure greatly improved predictions of empirical similarity judgments and feature ratings of contextually relevant concepts. Furthermore, we describe a novel, computationally tractable method for improving predictions of contextually-unconstrained embedding models based on dimensionality reduction of their internal representation to a small number of contextually relevant semantic features. By improving the correspondence between predictions derived automatically by machine learning methods using vast amounts of data and more limited, but direct empirical measurements of human judgments, our approach may help leverage the availability of online corpora to better understand the structure of human semantic representations and how people make judgments based on those. (shrink)

Cognitive Science, Volume 46, Issue 2, February 2022.

The ability to understand and communicate about the actions of others is a fundamental aspect of our daily activity. How can we talk about what others are doing? What qualities do different actions have such that they cause us to see them as being different or similar? What is the connection between what we see and the development of concepts and words or expressions for the things that we see? To what extent can two different people see and talk about (...) the same things? Is there a common basis for our perception, and is there then a common basis for the concepts we form and the way in which the concepts become lexicalized in language? The broad purpose of this thesis is to relate aspects of perception, categorization and language to action recognition and conceptualization. This is achieved by empirically demonstrating a prototype structure for action categories and by revealing the effect this structure has on language via the semantic organization of verbs for natural actions. The results also show that implicit access to categorical information can affect the perceptual processing of basic actions. These findings indicate that our understanding of human actions is guided by the activation of high level information in the form of dynamic action templates or prototypes. More specifically, the first two empirical studies investigate the relation between perception and the hierarchical structure of action categories, i.e., subordinate, basic, and superordinate level action categories. Subjects generated lists of verbs based on perceptual criteria. Analyses based on multidimensional scaling showed a significant correlation for the semantic organization of a subset of the verbs for English and Swedish speaking subjects. Two additional experiments were performed in order to further determine the extent to which action categories exhibit graded structure, which would indicate the existence of prototypes for action categories. The results from typicality ratings and category verification showed that typicality judgments reliably predict category verification times for instances of different actions. Finally, the results from a repetition priming paradigm suggest that high level information about the categorical differences between actions can be implicitly activated and facilitates the later visual processing of displays of biological motion. This facilitation occurs for upright displays, but appears to be lacking for displays that are shown upside down. These results show that the implicit activation of information about action categories can play a critical role in the perception of human actions. (shrink)