Cognitive Psychology seminars

Reward expectations – one’s prediction about the likelihood of future outcomes - play a central role in shaping the satisfaction derived from those outcomes. Most existing research treats expectations as static, assuming they remain fixed in time. However, real-life expectations are often dynamic, fluctuating as new information becomes available. For example, during a soccer game, your expectations of seeing your team winning will likely rise and fall as the game unfolds. In the main part of this talk, I will present a series of studies demonstrating that human expectations can be tracked at sub-second timescales. Using slot machines as a case study, we leverage the continuous deceleration of the reels to elicit moment-by-moment fluctuations in rewardexpectations. To capture these dynamics, we take complementary approaches: we use the high temporal resolution of electroencephalography (EEG) to track neural signatures of evolving expectations, and we develop a novel behavioral paradigm (“Slot or Not”) designed to measure changes in expectations via betting behavior. Across four studies, we show that expectations fluctuate continuously and can be tracked both behaviorally and neurally. Extending these findings, a subsequent intracranial study shows that the human orbitofrontal cortex (OFC) encodes the moment-by-moment changes of reward expectations. In the second part of this talk, I will return to the relationship between expectations andsatisfaction. If expectations shape satisfaction, and if they are best conceptualized as dynamic trajectories rather than static quantities, a key question arises: does the trajectory leading up to an outcome influence how that outcome is evaluated? I will outline a new research direction aimed at formalizing this relationship using computational modeling. This is ongoing work, and I welcome feedback on how best to formalize these ideas. Finally, I will discuss potential extensions of this framework to psychopathology, asking whether alterations in dynamic expectations may characterize conditions such as Major Depressive Disorder and Gambling disorder. Together, this work introduces a new framework for studying expectations as dynamic processes, offering a richer understanding Presented in the van Vreeswijk Theoretical Neuroscience Seminar series (formerly WWTNS) on 2026-04-29. Recording duration: 00:42:25.

In cognitive development, learning more than the input provides is a central challenge. This challenge is especially evident in learning the meaning of numbers. Integers – and the quantities they denote – are potentially infinite, as are the fractional values between every integer. Yet children’s experiences of numbers are necessarily finite. Analogy is a powerful learning mechanism for children to learn novel, abstract concepts from only limited input. However, retrieving proper analogy requires cognitive supports. In this talk, I seek to propose and examine number lines as a mathematical schema of the number system to facilitate both the development of rational number understanding and analogical reasoning. To examine these hypotheses, I will present a series of educational intervention studies with third-to-fifth graders. Results showed that a short, unsupervised intervention of spatial alignment between integers and fractions on number lines produced broad and durable gains in fractional magnitudes. Additionally, training on conceptual knowledge of fractions – that fractions denote magnitude and can be placed on number lines – facilitates explicit analogical reasoning. Together, these studies indicate that analogies can play an important role in rational number learning with the help of number lines as schemas. These studies shed light on helpful practices in STEM education curricula and instructions.

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.

Analogies between old and new concepts are common during classroom instruction. While previous studies of transfer focus on how features of initial learning guide later transfer to new problem solving, less is known about how to best support analogical transfer from previous learning while children are engaged in new learning episodes. Such research may have important implications for teaching and learning in mathematics, which often includes analogies between old and new information. Some existing research promotes supporting learners' explicit connections across old and new information within an analogy. In this talk, I will present evidence that instructors can invite implicit analogical reasoning through warm-up activities designed to activate relevant prior knowledge. Warm-up activities "close the transfer space" between old and new learning without additional direct instruction.

The predictive map hypothesis provides a promising framework to model representations in the hippocampal formation. I will introduce a tractable implementation of a predictive map called the successor representation (SR), before presenting data showing that rats and humans display SR-like navigational choices on a novel open-field maze. Next, I will show how such a predictive map could be implemented using spatial representations found in the hippocampal formation, before finally presenting how such learning might be well approximated by phenomena that exist in the spatial memory system - namely spike-timing dependent plasticity and theta phase precession.

Space is the universal donor for relations" (Gentner, 2014). This quote is the foundation of my talk. I will explore how and why visual representations and analogies are related, and why. I will also explore how considering the relation between analogy and spatial reasoning can shed light on why and how spatial thinking is correlated with learning in STEM fields. For example, I will consider children’s numbers sense and learning of the number line from the perspective of analogical reasoning.

A core question in human development is how we bring meaning to conventional symbols. This question is deeply connected to understanding how children learn mathematics—a symbol system with unique vocabularies, syntaxes, and written forms. In this talk, I will present findings from a program of research focused on children’s acquisition of place value symbols (i.e., multidigit number meanings). The base-10 symbol system presents a variety of obstacles to children, particularly in English. Children who cannot overcome these obstacles face years of struggle as they progress through the mathematics curriculum of the upper elementary and middle school grades. Through a combination of longitudinal, cross-sectional, and pretest-training-posttest approaches, I aim to illuminate relational learning mechanisms by which children sometimes succeed in mastering the place value system, as well as instructional techniques we might use to help those who do not.

Playing action video games involves both explicit (conscious) and implicit (non-conscious) expectations of timed events, such as the appearance of foes. While studies revealed that explicit attention skills are improved in action video game players (VGPs), their implicit skills remained untested. To this end, we investigated explicit and implicit temporal processing in VGPs and non-VGPs (control participants). In our variable foreperiod task, participants were immersed in a virtual reality and instructed to respond to a visual target appearing at variable delays after a cue. I will present behavioral, oculomotor and EEG data and discuss possible markers of the implicit passage of time and explicit temporal attention processing. All evidence indicates that VGPs have enhanced implicit skills to track the passage of time, which does not require conscious attention. Thus, action video game play may improve a temporal processing found altered in psychopathologies, such as schizophrenia. Could digital (game-based) interventions help remediate temporal processing deficits in psychiatric populations?

Comparison is a powerful learning process that improves learning in many domains. For over 10 years, my colleagues and I have researched how we can use comparison to support better learning of school mathematics within classroom settings. In 5 short-term experimental, classroom-based studies, we evaluated comparison of solution methods for supporting mathematics knowledge and tested whether prior knowledge impacted effectiveness. We next developed supplemental Algebra I curriculum and professional development for teachers to integrate Comparison and Explanation of Multiple Strategies (CEMS) in their classrooms and tested the promise of the approach when implemented by teachers in two studies. Benefits and challenges emerged in these studies. I will conclude with evidence-based guidelines for effectively supporting comparison and explanation in the classroom. Overall, this program of research illustrates how cognitive science research can guide the design of effective educational materials as well as challenges that occur when bridging from cognitive science research to classroom instruction.

The eyes send a continuous stream of about two million nerve fibers to the brain, but only a fraction of this information is stored as visual memories. This talk will detail three neurocomputational models that attempt an understanding how the visual system makes on-the-fly decisions about how to encode that information. First, the STST family of models (Bowman & Wyble 2007; Wyble, Potter, Bowman & Nieuwenstein 2011) proposes mechanisms for temporal segmentation of continuous input. The conclusion of this work is that the visual system has mechanisms for rapidly creating brief episodes of attention that highlight important moments in time, and also separates each episode from temporally adjacent neighbors to benefit learning. Next, the RAGNAROC model (Wyble et al. 2019) describes a decision process for determining the spatial focus (or foci) of attention in a spatiotopic field and the neural mechanisms that provide enhancement of targets and suppression of highly distracting information. This work highlights the importance of integrating behavioral and electrophysiological data to provide empirical constraints on a neurally plausible model of spatial attention. The model also highlights how a neural circuit can make decisions in a continuous space, rather than among discrete alternatives. Finally, the binding pool (Swan & Wyble 2014; Hedayati, O’Donnell, Wyble in Prep) provides a mechanism for selectively encoding specific attributes (i.e. color, shape, category) of a visual object to be stored in a consolidated memory representation. The binding pool is akin to a holographic memory system that layers representations of select latent representations corresponding to different attributes of a given object. Moreover, it can bind features into distinct objects by linking them to token placeholders. Future work looks toward combining these models into a coherent framework for understanding the full measure of on-the-fly attentional mechanisms and how they improve learning.

According to the concreteness fading approach, instruction should start with concrete representations and progress stepwise to representations that are more idealized. Various researchers have suggested that concreteness fading is a broadly applicable instructional approach. In this talk, we conceptually analyze examples of concreteness fading in mathematics and various science domains. In this analysis, we draw on theories of analogical and relational reasoning and on the literature about learning with multiple representations. Furthermore, we report on an experimental study in which we employed concreteness fading in advanced physics education. The results of the conceptual analysis and the experimental study indicate that concreteness fading may not be as generalizable as has been suggested. The reasons for this limited generalizability are twofold. First, the types of representations and the relations between them differ across different domains. Second, the instructional goals between domains and the subsequent roles of the representations vary.

Research on analogical processing and reasoning has provided strong evidence that the use of adequate educational analogies has strong and positive effects on the learning of mathematics. In this talk I will show some experimental results suggesting that analogies based on spatial representations might be particularly effective to improve mathematics learning. Since fostering mathematics learning also involves addressing psychosocial factors such as the development of mathematical anxiety, providing social incentives to learn, and fostering engagement and motivation, I will argue that one area to explore with great potential to improve math learning is applying analogical research in the development of learning games aimed to improve math learning. Finally, I will show some early prototypes of an educational project devoted to developing games designed to foster the learning of early mathematics in kindergarten children.

Learning by analogy is a powerful tool children’s developmental repertoire, as well as in educational contexts such as mathematics, where the key knowledge base involves building flexible schemas. However, noticing and learning from analogies develops over time and is cognitively resource intensive. I review studies that provide insight into the relationship between mechanisms driving children’s developing analogy skills, highlighting environmental inputs (parent talk and prior experiences priming attention to relations) and neuro-cognitive factors (Executive Functions and brain injury). I then note implications for mathematics learning, reviewing experimental findings that show analogy can improve learning, but also that both individual differences in EFs and environmental factors that reduce available EFs such as performance pressure can predict student learning.

It is a truth universally acknowledged that relational reasoning is important for learning in Science, Technology, Engineering, and Mathematics (STEM) disciplines. However, much research on relational reasoning uses examples unrelated to STEM concepts (understandably, to control for prior knowledge in many cases). In this talk I will discuss how real STEM concepts can be profitably used in relational reasoning research, using fraction concepts in mathematics as an example.