mental representation
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Mechanisms of relational structure mapping across analogy tasks
Following the seminal structure mapping theory by Dedre Gentner, the process of mapping the corresponding structures of relations defining two analogs has been understood as a key component of analogy making. However, not without a merit, in recent years some semantic, pragmatic, and perceptual aspects of analogy mapping attracted primary attention of analogy researchers. For almost a decade, our team have been re-focusing on relational structure mapping, investigating its potential mechanisms across various analogy tasks, both abstract (semantically-lean) and more concrete (semantically-rich), using diverse methods (behavioral, correlational, eye-tracking, EEG). I will present the overview of our main findings. They suggest that structure mapping (1) consists of an incremental construction of the ultimate mental representation, (2) which strongly depends on working memory resources and reasoning ability, (3) even if as little as a single trivial relation needs to be represented mentally. The effective mapping (4) is related to the slowest brain rhythm – the delta band (around 2-3 Hz) – suggesting its highly integrative nature. Finally, we have developed a new task – Graph Mapping – which involves pure mapping of two explicit relational structures. This task allows for precise investigation and manipulation of the mapping process in experiments, as well as is one of the best proxies of individual differences in reasoning ability. Structure mapping is as crucial to analogy as Gentner advocated, and perhaps it is crucial to cognition in general.
Modelling metaphor comprehension as a form of analogizing
What do people do when they comprehend language in discourse? According to many psychologists, they build and maintain cognitive representations of utterances in four complementary mental models for discourse that interact with each other: the surface text, the text base, the situation model, and the context model. When people encounter metaphors in these utterances, they need to incorporate them into each of these mental representations for the discourse. Since influential metaphor theories define metaphor as a form of (figurative) analogy, involving cross-domain mapping of a smaller or greater extent, the general expectation has been that metaphor comprehension is also based on analogizing. This expectation, however, has been partly borne out by the data, but not completely. There is no one-to-one relationship between metaphor as (conceptual) structure (analogy) and metaphor as (psychological) process (analogizing). According to Deliberate Metaphor Theory (DMT), only some metaphors are handled by analogy. Instead, most metaphors are presumably handled by lexical disambiguation. This is a hypothesis that brings together most metaphor research in a provocatively new way: it means that most metaphors are not processed metaphorically, which produces a paradox of metaphor. In this talk I will sketch out how this paradox arises and how it can be resolved by a new version of DMT, which I have described in my forthcoming book Slowing metaphor down: Updating Deliberate Metaphor Theory (currently under review). In this theory, the distinction between, but also the relation between, analogy in metaphorical structure versus analogy in metaphorical process is of central importance.
Navigating Increasing Levels of Relational Complexity: Perceptual, Analogical, and System Mappings
Relational thinking involves comparing abstract relationships between mental representations that vary in complexity; however, this complexity is rarely made explicit during everyday comparisons. This study explored how people naturally navigate relational complexity and interference using a novel relational match-to-sample (RMTS) task with both minimal and relationally directed instruction to observe changes in performance across three levels of relational complexity: perceptual, analogy, and system mappings. Individual working memory and relational abilities were examined to understand RMTS performance and susceptibility to interfering relational structures. Trials were presented without practice across four blocks and participants received feedback after each attempt to guide learning. Experiment 1 instructed participants to select the target that best matched the sample, while Experiment 2 additionally directed participants’ attention to same and different relations. Participants in Experiment 2 demonstrated improved performance when solving analogical mappings, suggesting that directing attention to relational characteristics affected behavior. Higher performing participants—those above chance performance on the final block of system mappings—solved more analogical RMTS problems and had greater visuospatial working memory, abstraction, verbal analogy, and scene analogy scores compared to lower performers. Lower performers were less dynamic in their performance across blocks and demonstrated negative relationships between analogy and system mapping accuracy, suggesting increased interference between these relational structures. Participant performance on RMTS problems did not change monotonically with relational complexity, suggesting that increases in relational complexity places nonlinear demands on working memory. We argue that competing relational information causes additional interference, especially in individuals with lower executive function abilities.
It’s not over our heads: Why human language needs a body
n the ‘orthodox’ view, cognition has been seen as manipulation of symbolic, mental representations, separate from the body. This dualist Cartesian approach characterised much of twentieth-century thought and is still taken for granted by many people today. Language, too, has for a long time been treated across scientific domains as a system operating largely independently from perception, action, and the body (articulatory-perceptual organs notwithstanding). This could lead one into believing that to emulate linguistic behaviour, it would suffice to develop ‘software’ operating on abstract representations that would work on any computational machine. Yet the brain is not the sole problem-solving resource we have at our disposal. The disembodied picture is inaccurate for numerous reasons, which will be presented addressing the issue of the indissoluble link between cognition, language, body, and environment in understanding and learning. The talk will conclude with implications and suggestions for pedagogy, relevant for disciplines as diverse as instruction in language, mathematics, and sports.
A new experimental paradigm to study analogy transfer
Analogical reasoning is one of the most complex cognitive functions in humans that allows abstract thinking, high-level reasoning, and learning. Based on analogical reasoning, one can extract an abstract and general concept (i.e., an analogy schema) from a familiar situation and apply it to a new context or domain (i.e., analogy transfer). These processes allow us to solve problems we never encountered before and generate new ideas. However, the place of analogy transfer in problem solving mechanisms is unclear. This presentation will describe several experiments with three main findings. First, we show how analogy transfer facilitates problem-solving, replicating existing empirical data largely based on the radiation/fortress problems with four new riddles. Second, we propose a new experimental task that allows us to quantify analogy transfer. Finally, using science network methodology, we show how restructuring the mental representation of a problem can predict successful solving of an analogous problem. These results shed new light on the cognitive mechanism underlying solution transfer by analogy and provide a new tool to quantify individual abilities.
Cognitive Maps
Ample evidence suggests that the brain generates internal simulations of the outside world to guide our thoughts and actions. These mental representations, or cognitive maps, are thought to be essential for our very comprehension of reality. I will discuss what is known about the informational structure of cognitive maps, their neural underpinnings, and how they relate to behavior, evolution, disease, and the current revolution in artificial intelligence.
Reasoning Ability: Neural Mechanisms, Development, and Plasticity
Relational thinking, or the process of identifying and integrating relations between mental representations, is regularly invoked during reasoning. This mental capacity enables us to draw higher-order abstractions and generalize across situations and contexts, and we have argued that it should be included in the pantheon of executive functions. In this talk, I will briefly review our lab's work characterizing the roles of lateral prefrontal and parietal regions in relational thinking. I will then discuss structural and functional predictors of individual differences and developmental changes in reasoning.
NMC4 Short Talk: Untangling Contributions of Distinct Features of Images to Object Processing in Inferotemporal Cortex
How do humans perceive daily objects of various features and categorize these seemingly intuitive and effortless mental representations? Prior literature focusing on the role of the inferotemporal region (IT) has revealed object category clustering that is consistent with the semantic predefined structure (superordinate, ordinate, subordinate). It has however been debated whether the neural signals in the IT regions are a reflection of such categorical hierarchy [Wen et al.,2018; Bracci et al., 2017]. Visual attributes of images that correlated with semantic and category dimensions may have confounded these prior results. Our study aimed to address this debate by building and comparing models using the DNN AlexNet, to explain the variance in representational dissimilarity matrix (RDM) of neural signals in the IT region. We found that mid and high level perceptual attributes of the DNN model contribute the most to neural RDMs in the IT region. Semantic categories, as in predefined structure, were moderately correlated with mid to high DNN layers (r = [0.24 - 0.36]). Variance partitioning analysis also showed that the IT neural representations were mostly explained by DNN layers, while semantic categorical RDMs brought little additional information. In light of these results, we propose future works should focus more on the specific role IT plays in facilitating the extraction and coding of visual features that lead to the emergence of categorical conceptualizations.
Thalamocortical circuits from neuroanatomy to mental representations
In highly volatile environments, performing actions that address current needs and desires is an ongoing challenge for living organisms. For example, the predictive value of environmental signals needs to be updated when predicted and actual outcomes differ. Furthermore, organisms also need to gain control over the environment through actions that are expected to produce specific outcomes. The data to be presented will show that these processes are highly reliant on thalamocortical circuits wherein thalamic nuclei make a critical contribution to adaptive decision-making, challenging the view that the thalamus only acts as a relay station for the cortical stage. Over the past few years, our work has highlighted the specific contribution of multiple thalamic nuclei in the ability to update the predictive link between events or the causal link between actions and their outcomes via the combination of targeted thalamic interventions (lesion, chemogenetics, disconnections) with behavioral procedures rooted in experimental psychology. We argue that several features of thalamocortical architecture are consistent with a prominent role for thalamic nuclei in shaping mental representations.
Time perception: how our judgment of time is influenced by the regularity and change in stimulus distribution?
To organize various experiences in a coherent mental representation, we need to properly estimate the duration and temporal order of different events. Yet, our perception of time is noisy and vulnerable to various illusions. Studying these illusions can elucidate the mechanism by which the brain perceives time. In this talk, I will review a few studies on how the brain perceives duration of events and the temporal order between self-generated motion and sensory feedback. Combined with computational models at different levels, these experiments illustrated that the brain incorporates the prior knowledge of the statistical distribution of the duration of stimuli and the decay of memory when estimating duration of an individual event, and adjusts its perception of temporal order to changes in the statistics of the environment.
mental representation coverage
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