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Articles 1 - 5 of 5
Full-Text Articles in Cognitive Science
A Geometric Framework For Modeling Real-World Experience, Knowledge, Learning, And Memory, Paxton C. Fitzpatrick
A Geometric Framework For Modeling Real-World Experience, Knowledge, Learning, And Memory, Paxton C. Fitzpatrick
Dartmouth College Ph.D Dissertations
A growing body of recent work highlights the importance of studying learning and memory in “naturalistic” contexts that reflect how these processes function in our day-to-day lives. Yet the incredible complexity of the world around us, and of the idiosyncratic ways we learn from and remember it, make characterizing the dynamics of learning and memory for real-world experiences challenging. I present a computational framework that leverages the embedding representations of language models to cast experiences and memories as high-dimensional trajectories unfolding through a common representation space, enabling them to be directly related and compared via their latent semantic geometries. I …
Distributed Impressions: How Multiple Minds Come Together To Shape Person Perception, Lindsey J. Tepfer
Distributed Impressions: How Multiple Minds Come Together To Shape Person Perception, Lindsey J. Tepfer
Dartmouth College Ph.D Dissertations
Moments after perceiving another person, we immediately infer a wealth of information about them. Despite the complexities within our social environments, we distill an incredible magnitude of details available to us into compressed representations of other people’s minds and mannerisms. Yet research has focused largely on mapping isolated stimuli—divorced from its messy context—to the spontaneous impressions they provoke. As a result, there are many unanswered questions about how our judgments are influenced by the rich and noisy social world we inhabit. Here, I’ve leveraged two paradigms to investigate how impression formation and updating may operate when the constraints of the …
Understanding Behavioral And Representational Divergences Of Humans And Machines, Thomas Lasman Botch
Understanding Behavioral And Representational Divergences Of Humans And Machines, Thomas Lasman Botch
Dartmouth College Ph.D Dissertations
Human behavior and cognition are strikingly variable: people differ from one another in their preferences and abilities, and even from themselves across situations. Yet this diversity arises from common neural machinery shaped by the complex environments humans inhabit. A central objective of cognitive neuroscience is to understand how this varied experience emerges from interactions between brains, agents, and environments. In this dissertation, I argue that comparing behavior and neural computation across humans, artificial systems, and contexts is essential for understanding the flexibility of human cognition. Across three chapters, I use this comparative approach to examine how the rich, multimodal contexts …
From Meaning To Memory: Assessing The Capacity And Representational Structure Of Visual Working Memory With Meaningful Stimuli, Yong Hoon Chung
From Meaning To Memory: Assessing The Capacity And Representational Structure Of Visual Working Memory With Meaningful Stimuli, Yong Hoon Chung
Dartmouth College Ph.D Dissertations
Visual working memory is thought to be strictly limited. Yet we remember meaningful, real-world objects better than abstract stimuli. Here I show that this advantage arises from the semantic structure of meaningful objects, not their perceptual features alone, and that it extends even to memory for associated features such as color. In the brain, meaningful objects elicit greater and more distributed delay activity, consistent with the recruitment of higher-level neural processes during maintenance. I propose that semantic knowledge adds representational dimensions that make items more distinctive, and that these dimensions are organized hierarchically with lower-level visual features. These findings recast …
Epistemic Mentalizing And Causal Cognition Across Agents And Objects, Bryan S. Gonzalez
Epistemic Mentalizing And Causal Cognition Across Agents And Objects, Bryan S. Gonzalez
Dartmouth College Ph.D Dissertations
This dissertation examines mentalizing abilities, causal reasoning, and the interactions thereof. Minds are so much more than false beliefs, yet much of the existing research on mentalizing has placed a disproportionately large emphasis on this one aspect of mental life. The first aim of this dissertation is to examine whether representing others’ knowledge states relies on more fundamentally basic cognitive processes than representations of their mere beliefs. Using a mixture of behavioral and brain measures across five experiments, I find evidence that we can represent others' knowledge quicker and using fewer neural resources than when representing others’ beliefs. To be …