testing Local Recurrency First Order Theory
This branch of the ARC-FoHo project uses a combination of psychophysics, analytical process development, and computational neuroimaging approaches (fMRI) in healthy adult humans to evaluate whether first-order local recurrency signals in early visual cortical areas are sufficient to explain the strength of our subjective experiences of visual stimuli.
We have recently put out a preprint of the first phase of our project:
Attention robustly dissociates objective performance and subjective visibility reports
Authors: Karen J. Tian*, Brian Maniscalco*, Michael L. Epstein, Angela Shen, Olenka Graham Castaneda, Taiga Kurosawa, Jennifer A. Motzer, Emil Olsson, Emily E. Russell, Meghan E. Walsh, Juneau Wang, Tugral Bek Awrang Zeb, Richard Brown, Victor A. F. Lamme, Hakwan Lau, Biyu J. He, Jan W. Brascamp, Ned Block, David Chalmers, Megan A. K. Peters†, & Rachel N. Denison† (*co-first, †co-senior)
We also have a preprint on the Relative Psychometric Function method used in this project:
Authors: Brian Maniscalco, Olenka Graham Castaneda, Brian Odegaard, Jorge Morales, Sivananda Rajananda, Rachel Denison, and Megan A. K. Peters
University of California Irvine
Boston University
Karen Tian (BU)
Brian Maniscalco (UCI)
Michael Epstein (BU)
Emil Olsson (UCI)
Angela Shen (UCI)
Olenka Graham Castaneda (UCI)
Jennifer Motzer (BU)
Juneau Wang (BU)
Emily Russell (BU)
Meghan Walsh (BU)
Tugral Bek Awrang Zeb (UCI)
Lizbeth Romero (UCI)
Giancarlo Arzu (UCI)
Meera Sriram (UCI)
Minh Nguyen (UCI)