Rachel Chen

Curriculum Vitae

Education

New York University

2024 โ€“ Present

Ph.D. in Cognition & Perception (Quantitative Concentration)

PI: Prof. Michael S. Landy

Research focus: Computational models of multisensory recalibration and sensorimotor planning

New York University

2022 โ€“ 2024

M.S. in Psychology, concentration in Cognitive Neuroscience

PI: Prof. Marisa Carrasco

Research focus: Neural correlates of covert spatial attention and mechanisms of human visual perceptual properties

The University of British Columbia

2017 โ€“ 2021

B.A. in Psychology and Behavioral Neuroscience

Experience

Using Transcranial Magnetic Stimulation (๐Ÿ”— TMS) and orientation discrimination tasks, we examined whether the rFEF+ (๐Ÿ”— the putative human homolog of the right macaque frontal eye field) is a critical neural correlate for exogenous attention. By measuring contrast-response functions (CRFs) and perceptual sensitivity, we found that stimulating the rFEF+ did not eliminate the exogenous attentional gain. These results complete a double dissociation between rFEF+ and V1/V2, providing evidence that voluntary and involuntary spatial attention are mediated by separate system-level computations and neural pathways.

This project investigated the system-level computations underlying perceptual heterogeneities across eccentricity and polar angle. Using the equivalent noise method (Pelli D.G. 1981, Lu Z.-L. & Dosher B.A. 2008) and the Perceptual Template Mode (Lu Z.-L. & Dosher B.A. 1998), we modeled how gain, internal noise, and nonlinearity affect orientation discrimination. Our study found that while eccentricity effects are driven by multiple computational factors, polar angle asymmetries are uniquely tied to variations in gainโ€”paralleling known distributions of neuronal count in the visual cortex.

This project utilizes ๐Ÿ”— Virtual Reality to investigate whether people have internal estimation of their motor noise during 3D reaching movements. Using an open-loop design to minimize visual feedback and maximize reliance on internal models, we tested how participants shift their aim points in response to penalty regions placed along different spatial axes. The results provide insight into whether human motor planning accounts for the directional covariance of motor noise.

This project conducted clinical neuroscience research on memory consolidation in epilepsy patients during my time at the ๐Ÿ”— NYU Grossman School of Medicine. I performed EEG analysis and automated Persyst spike detection to investigate the mechanisms behind accelerated long-term forgetting in epilepsy patients.

This investigation explored the dissociation between symbolic and situational mathematical abilities across development. We used online and offline tasks and assessed 183 sixth-graders and 180 seventh-to-eighth-graders. Our results revealed that while symbolic ability (e.g., fraction division, number series) increases with age, situational ability (e.g., constructing appropriate contexts for arithmetic formulas) actually declines. These findings suggest that current educational scaffolds prioritize procedural computation over conceptual application, necessitating a re-evaluation of math curricula to bridge this developmental lag.

Skills

Programming Languages: MATLAB, Python (NumPy, SciPy, Pandas), R

Experimental Techniques: Psychophysics, Eye-tracking, Unity/VR, Transcranial Magnetic Stimulation

Experimental Design: A/B Testing, Survey Design, Online Data Collection

Awards and Honors

NYU Graduate School of Arts and Science MacCracken Fellowship

NYU 2025 Dean's Conference Fund Award

NYU Graduate Student Research Conference Award

Teaching

Undergraduate Social Neuroscience

Fall 2023

Undergraduate Perception

Spring 2024

Undergraduate Fundamental Statistics

Summer 2025