Friday, May 16, 2025, 5:15 – 7:15 pm, Talk Room 2

Organizers: Preeti Verghese¹, Marisa Carrasco², David Melcher³ (¹Smith-Kettlewell Eye Research Institute, ²New York University, ³New York University, Abu Dhabi)
Speakers: Preeti Verghese, Marisa Carrasco, Mike Landy, Barbara Anne Dosher, David Melcher, Mary Hayhoe, Rich Krauzlis, Jie Z. Wang, Jacob Feldman

Introduction: 5:15 pm

Preeti Verghese¹, Marisa Carrasco²; ¹Smith-Kettlewell Eye Research Institute, ²New York University

Eileen & VSS: 5:20 pm

Michael Landy, New York University

Talk 1: 5:25 pm

 “Cogito Ergo Moveo”—The role of cognition and attention in eye movements in the work of Eileen Kowler

Barbara Anne Dosher, University of California, Irvine

“I think therefore I move”, she titled one review paper (Kowler, 1996). One key strand of Eileen Kowler’s research revealed how attention and expectation engage eye movements to serve the needs of vision. Her experimental interventions expanded models of the control of eye movements beyond early models that “assume[d] that eye movements are driven by low-level sensory signals, such as retinal image position or retinal motion”.  She investigated how higher-level cognitive knowledge and goals influence behavior to optimize information acquisition by the eye. Key examples of this work include the role of attention and selection in smooth pursuit, the interaction of attention and perception in single eye movements, and the dynamics of attention used to guide sequences of eye movements. This talk considers some of these findings.

Talk 2: 5:40 pm

What visual representation guides saccades? Reflections on “Shapes, Surfaces and Saccades” (Melcher & Kowler, 1999)

David Melcher, New York University, Abu Dhabi

Back when eye tracking required an entire room full of machinery, pioneering research on the oculomotor system investigated fixational and saccadic eye movements for simple targets, like fixation points, crosses or disks. A series of studies in the 1990’s indicated that, for simple outline shapes, saccades landed near the center-of-gravity. These studies had suggested a relatively primitive representation of the visual target, prior to the linking of elements into contours and shapes. In a series of six experiments, we showed that the saccadic landing position was predicted by the center-of-area of a surface defined by the shape boundary. This finding followed a line of Eileen Kowler’s research showing that eye movements are not merely reflexive, but instead reflect complex visual and cognitive processing. As research has now progressed into the 21st century, key ideas from this 1999 paper have been expanded into studies of natural and 3D scene perception, trans-saccadic object feature prediction, ensemble processing, smooth pursuit, and grasping movements, among other topics. Still, there remain fundamental questions about how sensory and motor systems interact, and to what extent the oculomotor system reflects, and differs from, our conscious visual perceptual experience.

Talk 3: 5:55 pm

Understanding Natural Vision

Mary Hayhoe, University of Texas, Austin

At a time when much eye movement research was dominated by a stimulus driven, linear systems approach, Eileen Kowler demonstrated that eye movement control is intrinsically connected to a range of cognitive processes such as attention, memory, prediction, planning, and scene understanding. She also understood that this is a natural consequence of the fact that eye movements are embedded in ongoing actions, and argued for measuring eye movements in the context of unconstrained behavior. As the eye and body tracking technology have developed, we can measure the operation of these cognitive processes in more diverse contexts, and this has allowed a more unified view of visuo-motor control. If we assume that the job of vision is to provide information for selecting suitable actions, we can view gaze control as part of complex sequential decision processes in the service of goal-directed behavior. In natural behavior, even the simplest actions involve both long and short-term memory, evaluation of sensory and motor uncertainties and costs, and planning that takes place over time scales of seconds in the context of action sequences. Consequently, a decision theoretic context allows a more coordinated approach to understanding natural visually guided behavior.

Talk 4: 6:10 pm

Opening the window from eye movements to cognitive expectations and visual perception

Rich Krauzlis, Laboratory of Sensorimotor Research, National Eye Institute

There was a time not so long ago when eye movements were not widely appreciated as providing windows into visual cognition and perception. Instead, they were viewed mostly as motor reactions to visual “error” signals. This engineering perspective was spectacularly successful in ferreting out the basic principles for smooth pursuit and other eye movements, but it did not easily accommodate non-sensory and non-motor factors. Against this backdrop, Eileen made a series of seminal observations starting with her thesis work, showing that cognitive expectations exert strong influences on smooth pursuit eye movements. Her experimental designs were wonderfully creative and established that there is much more going on in the pursuit system than can be found slipping across the retina. Her results sparked controversy at the time, but her conclusions are now broadly accepted: smooth pursuit is guided not only by low-level visual inputs, but also by higher-level visual processes related to expectations, memory, and cognition. These conclusions now seem almost self-evident, but in fact they took a great deal of perseverance and ingenuity. Eileen should be lauded not only for the significance of her scientific accomplishments, but also for the example she provided of an independent and courageous intellect.

Talk 5: 6:25 pm

Predictive smooth pursuit eye movements reflect knowledge of Newtonian mechanics

Jie Z. Wang¹, Abdul-Rahim Deeb², Fulvio Domini³, Eileen Kowler⁴

¹ University of Rochester, ² John Hopkins University, ³ Brown University, ⁴ Rutgers University-New Brunswick

Smooth pursuit employs a variety of cues to predict the future motion of a moving target, enabling timely and accurate tracking. Since real-world motions often obey the Newtonian mechanics, an implicit understanding of these laws should be a particularly effective cue for facilitating anticipation in pursuit. In this study, we focus on understanding how 2-D smooth pursuit incorporates Newtonian mechanics to interpret and predict future motion. We examined the tracking of a “target object” whose motion path appeared to be due to a collision with a moving “launcher object”. The direction of post-collision target motion was either consistent with or deviated from the Newtonian prediction. Newtonian and non-Newtonian paths were run in separate blocks allowing observers the opportunity to predict and learn the target’s path based on the launcher’s movement. Anticipatory pursuit was found to be faster and more precise when post-collision paths conformed to predictions of Newtonian mechanics. Even when there was  ample opportunity to learn the non-Newtonian motion paths, there was evidence of a bias in the direction of the Newtonian prediction. These findings support the idea that smooth pursuit can leverage the regularities in everyday physical events to formulate predictions about future motion. These predictive capabilities of smooth pursuit result in increased compatibility with natural motions and thereby allow for more accurate and efficient tracking of real-world movements.

Talk 6: 6:40 pm

Decisions and eye movements in a dynamic naturalistic VR task (response to Kowler, 1995, personal communication)

Jacob Feldman, Rutgers University

(Joint work with Jakub Suchojad, Sam Sohn, Michelle Shlivko, and Karin Stromswold) 

One of the main goals of cognitive research, continually emphasized by Eileen Kowler, is to understand behavior in realistic, natural contexts. In this talk I’ll talk about a ubiquitous natural task that we have recently studied in virtual reality (VR): social wayfinding. Social wayfinding refers to the way people navigate through environments that contain other people, like a crowded train station. In addition to various generic motivations, like the desire to minimize time and energy expended, this task involves a number of specifically social goals, like avoiding colliding with or rudely cutting off other people. We have been studying this problem in VR, asking our subjects to navigate around both static obstacles (e.g. couches) and dynamic ones (e.g. people walking around). We have also been collecting eye movements so as to better understand how subjects handle the very complex series of decisions they need to make as they move through the environment. Broadly speaking, we find that their eye movements reflect the hierarchical nature of the task, sometimes fixating on “local” obstacles and at other times on “global” features such as the target gate. I’ll end by commenting on how this work addresses (and also fails to address) a question that Eileen posed to me many years ago.

Open Mic: 6:55 — 7:15 pm

Saturday, May 17, 2025, 12:45 – 2:15 pm EDT, Banyan/Citrus

Organizers: Noah Britt (McMaster University); Victoria Jacoby, (Brigham and Women’s Hospital, Harvard Medical School); and Jes Parker (University of Tennessee-Knoxville)
Moderator: Geoffrey Boynton (University of Washington)
Speakers: Kirsten Adam (Rice University); Dennis Levi (University of California, Berkeley); Ming Meng (South China Normal University); Philipp Musfeld (University of Zurich)

The VSS-SPC invites you to a panel discussion on the role of open science in vision research and academic publishing. Invited speakers will explore the principles of open science—why it matters, how to implement it, and its impact on research transparency and reproducibility. We will also have additional speakers that will share and discuss how open science practices influence publishing and editorial processes in top peer-reviewed journals. The session will conclude with a valuable 30-minute Q&A, giving attendees the opportunity to engage directly with all our well-esteemed speakers. Join us for an insightful discussion on navigating open science, publishing high-quality research, and shaping the future of scholarly communication.

Geoffrey Boynton

University of Washington

Geoffrey Boynton, is a VSS Board Member and studies visual attention, reading and prosthetic vision. After studying mathematics at U.C. San Diego and U.C. Santa Barbara, Dr. Boynton received a PhD in Psychology and Cognitive Sciences at U.C. Santa Barbara in 1994. After a decade at the Salk Institute in La Jolla, CA, he joined the faculty at the University of Washington. In 2019 led an effort to develop a research MRI facility at the new Center for Human Neuroscience in the Department of Psychology which he now directs. He also teaches courses on visual perception and statistics.

Kirsten Adam

Rice University

Kirsten Adam is an Assistant Professor of Psychological Sciences at Rice University. Her work uses neural methods (EEG, fMRI) and behavior to characterize fundamental constraints on visual attention and working memory. Dr. Adam earned a B.S. in Biological Sciences at the University of Notre Dame, an M.S. in Cognitive Neuroscience at the University of Oregon, and a Ph.D. in Cognitive Psychology at the University of Chicago. Website: https://adamlab.rice.edu/

Dennis Levi

University of California, Berkeley

Dennis M. Levi is an American Professor at the University of California, Berkeley with appointments in the Herbert Wertheim School of Optometry & Vision Science, and the Helen Wills Neuroscience Institute. He received his diploma in Optometry in 1967 from the Witwatersrand School of Optometry, in Johannesburg, South Africa. His research focuses on how we see form and depth, and how these are impacted by abnormal early visual development, particularly amblyopia and strabismus. He has published more than 300 scientific papers and two books. His work has been cited almost 30,000 times and he has an h-index of 87 (Google Scholar). His research has been funded by the National Eye Institute (NEI) since 1976.

Monday, May 19, 2025, 2:30 – 4:00 pm EDT, Banyan/Citrus

Organizers: Akihito Maruya, State University of New York; Amy Bucklaew, University of Rochester; and Brady Roberts, University of Chicago (VSS Student-Postdoc Advisory Committee); Shin’ya Nishida (VSS Board of Directors)
Moderator: Akihito Maruya, State University of New York
Speakers: Frank Tong, Vanderbilt University; Michael F. Bonner, Johns Hopkins University; Kohitij Kar, York University

In recent years, AI has made remarkable progress, becoming increasingly accessible and implementable even for individuals without extensive expertise in computer science. Visual AI, a subset of artificial intelligence, empowers machines to interpret and understand the visual world. Recent advances have demonstrated AI’s value in modeling the visual cortex, predicting neural responses, simulating eye-tracking behavior, and analyzing psychophysical data. As AI technology becomes widely adopted, it is critical to understand the principles of its successes as well as its challenges.

This review begins by exploring how AI has empowered visual neuroscientists to unravel aspects of visual processing that were previously beyond reach. We will also examine how the similarity between AI and human vision can be quantified. While AI models can mimic human visual processing to some extent, they often produce percepts that deviate significantly from human perception, such as susceptibility to hallucinations or inversion effects. Understanding these differences raises an intriguing question: how can visual scientists help guide AI to align more closely with human visual perception? We will delve into the key differences between AI and human vision, uncover the reasons for these disparities—such as biases in training data and fundamental computational differences—and explore strategies to make AI systems emulate human visual processing more effectively.

Finally, while AI is a rapidly evolving technology with the potential to revolutionize research and innovation, it also brings substantial ethical challenges. For instance, when tools like ChatGPT generate code, the output is often built upon the contributions of others, yet those contributions may not be adequately recognized. This underscores the importance of addressing issues like training data bias, privacy concerns, and the steep learning curve required to grasp foundational AI principles. In this review, we will highlight these challenges and provide insights into fostering a deeper understanding of AI ethics, emphasizing the responsibility of integrating AI into scientific workflows thoughtfully and equitably.

Akihito Maruya

State University of New York

Akihito Maruya is a PhD student with Qasim Zaidi at the SUNY Graduate Center for Vision Research in NYC and Chair of the VSS Student-Postdoc Advisory Committee. He studies 3D perception in scenes and pictures, perception of rigid and non-rigid 3D objects, and form distortions perceived by adult and children amblyopes, using psychophysics and computational models.

Frank Tong

Vanderbilt University

Frank Tong is a Centennial Professor of Psychology and Professor of Ophthalmology and Visual Sciences at Vanderbilt University. He completed his PhD studies at Harvard University (1995-1999) working with Ken Nakayama and Nancy Kanwisher. His early research capitalized on functional MRI to investigate the neural bases of face processing and visual awareness, followed by the development of novel techniques to decode feature-selective responses from the human visual cortex to characterize their role in attentional selection and visual working memory. In recent years, he has been captivated by noteworthy similarities and striking divergences between the human visual system and current deep neural network models. His research has been recognized by YIA awards from the Vision Sciences Society, Cognitive Neuroscience Society, and the Troland Award from the National Academy of Sciences. Frank has previously served on the VSS Board of Directors and currently serves on the NIH Neuroscience of Basic Visual Processes study section panel.

Michael F. Bonner

Johns Hopkins University

Mick Bonner is an Assistant Professor of Cognitive Science at Johns Hopkins University, where he leads the Cognitive Neuroscience & Deep Learning Group. His work uses computational methods, including deep neural networks and advanced statistical techniques, in combination with neuroimaging and behavioral studies to understand the visual system of the human brain. The goal of this work is to identify the statistical principles that govern the representations of visual cortex and to build theoretically grounded models of how these representations are computed from sensory inputs. Before joining the Cognitive Science Department at Johns Hopkins, Mick completed a PhD in Neuroscience and a postdoctoral fellowship at the University of Pennsylvania.

Sunday, May 19, 2024, 1:00 – 2:00 pm EDT, Snowy Egret

Organizers: Claudia Damiano, University of Toronto and Stephanie Shields, University of Texas at Austin (VSS Student-Postdoc Advisory Committee); Jody Culham (VSS Board of Directors)
Moderator: Claudia Damiano, University of Toronto
Speakers: Robert Geirhos, Google DeepMind; Kim Meier, University of Houston; Joan Ongchoco, University of British Columbia: Woon Ju Park, University of Washington; Jake Whritner, Exponent

Back by popular demand! Following requests to repeat last year’s event, the VSS-SPC is hosting a panel discussion on early career transitions, from the undergraduate level up through securing faculty positions and jobs outside of academia. A panel of vision scientists with a variety of chosen career paths will discuss their stories, the transitions they’ve gone through in their careers, and how they made the key decisions that led them to their current jobs. After each panelist gives an overview of their story, audience members will be invited to participate in a question-and-answer session with the panel. The panel will include representatives from both academia and industry, so attendees will hear firsthand perspectives both on navigating academia and on transitioning between academia and industry. Especially given the recent layoffs in industry and the pandemic’s lasting impact on hiring in higher education, we hope the panel will provide useful insights into current trends affecting early career researchers and ideas for how trainees can increase their chances of success in today’s professional landscape.

Claudia Damiano (Moderator)

Postdoctoral Researcher, University of Toronto

Claudia Damiano is a Research Associate (senior postdoctoral researcher) at the University of Toronto, working with Dirk Bernhardt-Walther. She previously completed a postdoctoral fellowship in Leuven, Belgium, working with Johan Wagemans. Broadly, her research aims to understand how visual features impact aesthetic preferences and guide attention. Her work contributes to our understanding of the relationship between human perception and the appreciation of natural environments. Claudia has served as a panelist on similar early-career panels, offering advice to Master’s and PhD students about transitioning to a postdoc position. As a moderator, she will ensure that the panel offers valuable insights and actionable advice to attendees.