Six Dimensions of Dance Cognition. ABSTRACT: There is a growing body of work in philosophy, cognitive science, and neuroscience that tries to better understand the mind by examining it in the context of dance. Such work is often premised on the idea that dance demonstrates important, general, and underappreciated features of human thought. However, existing […]
How much do we know about visual representations? Quantifying the dimensionality gap between DNNs and visual cortex'. Abstract: Deep neural networks (DNNs) can explain a large portion of variance in image-evoked cortical responses by accounting for the highest variance latent dimensions in neural data, such as dimensions corresponding to animacy, aspect ratio, and curvature. However, […]
A group of graduate students and postdoctoral fellows from the Department of Cognitive Science at Johns Hopkins, are offering one-on-one mentoring about applying to our department, with priority given to prospective students from underrepresented groups. The sign up form will remain open until November 15, but we strongly encourage you to respond by November 5 for […]
Modeling shared and variable information encoded in fine-scale cortical topographies. ABSTRACT: Information is encoded in fine-scale functional topographies that vary from brain to brain. Hyperalignment models information that is shared across brain in a high-dimensional common information space. Hyperalignment transformations project idiosyncratic individual topographies into the common model information space. These transformations contain topographic basis functions, affording […]
Current MA student Atlas Kazemian will give a talk on "Toward a computational neuroscience of visual cortex without deep learning."
MA applications for Spring 2023 due.
Dog, cat, and leash: Difference in processing costs among inflectional allomorphs during speech production. Abstract: We need to generate contextually-appropriate inflections to produce well-formed words and sentences, and a key component of this process is generating the correct allomorph – variant pronunciations of a morpheme. In this project, we examine the processing costs of the English regular […]
The language system in the human brain. ABSTRACT: The goal of my research program is to understand the representations and computations that enable us to share complex thoughts with one another via language, and their neural implementation. A decade ago, I developed a robust new approach to the study of language in the brain based on identifying […]
PhD applications for Fall 2023 due as well as MA applications for Summer 2023 and Fall 2023 due.
Investigating compositional visual knowledge through challenging visual tasks ABSTRACT: Human vision manifests remarkable robustness to recognize objects from the visual world filled with a chaotic, dynamic assortment of information. Computationally, our visual system is challenged by the enormous variability in two-dimensional projected images as a function of viewpoint, lighting, material, articulation as well as occlusion. […]
Approximate Analysis by Synthesis: Towards a Computational Theory of Vision ABSTRACT: Vision is humans' underappreciated superpower. It gives us the miraculous ability to perceive the three-dimensional structure of the world from the complex pattern of light rays which are imaged on our retinas. Vision can be conceptualized as Analysis by Synthesis, formalized by Bayesian probability […]
Acquiring syntactic variation: regularization in wh-question production. ABSTRACT: Children are often exposed to language-internal variation. Studying the acquisition of variation allows us to understand more about children’s ability to acquire probabilistic input, their preferences at choice points, and factors contributing to such preference. Using wh-variation as a case study, this dissertation explores the acquisition of […]