Vision in Art and Neuroscience Fall 2024
9.72 (UG)
9.720 (G)
Tues & Thurs 3-5 pm in 10-150 (MIT Museum Studio)
contact: visualstudies AT mit.edu
The constructive nature of perception is at work in the gap between the observer and the outside – there, the world of experience is generated. From limited and noisy data incoming through the senses, our brains construct the rich world we perceive. Creating visual art throws that world of experience back to the outside, and in it we find reflected some mechanisms of the constructive process of vision. As such, we can find examples in art which allow us to “perceive perception.” Through readings, lecture, discussion, and project-based work, this course explore the neural and computational mechanisms of vision and their parallel manifestations in visual art. Working together, we will follow recipes for seeing to translate different levels of the visual processing hierarchy into the domain of experience, using the power of simple materials to foreground direct visual perception. The course is divided into one seminar-style lecture and one session of studio instruction per week. Each student will have access to studio materials and equipment for creating and documenting visual experiences. Students will be expected to prepare simple captures of work and work processes to share with the class as needed and to contribute to the exhibition content that will have physical and online aspects. A final project and exhibition of student work will replace a final exam.
Fall 2024 Syllabus (last updated 9/5/24)
Course Structure
The course consists of one two-hour seminar (Tuesday) and one two-hour studio workshop (Thursday) per week. Seminars will include slide talks, demonstrations, video documents, etc. by the team as well as invited guests. Carefully chosen readings and student presentations will fuel discussions. In previous years, workshop hours during the first weeks of class were spent in a dark room where students were guided through experiments visualizing the fundamental interactions of light and vision. As the semester progresses, studio sessions will serve preparation of final projects for exhibition. The seminar will be divided into six modules that build, one upon the next, to introduce principles of vision neuroscience and their parallels in the creation of visual art. Toward the end of the semester, we will design, install and open a public exhibition of projects in the Compton Gallery.
Online Catalogues of Past Work
See TOTAL INTERNAL REFLECTION, a virtual exhibition of work from our Fall 2020 course offering, online now!
Fall 2020 Recipes for Seeing
Perceiving Perception (December 2017 – February 2018), MIT Museum Studio Compton Gallery
Web Catalog
Dessert of the Real (December 2018 – May 2019), MIT Museum Studio Compton Gallery
Instruments of Vision (December 2019 – May 2020), MIT Museum Studio Compton Gallery
Emissive (December 2021 – fall 2022), MIT Museum Studio Compton Gallery
Course Modules
Module 1 The origins of structure in perception and art
Readings: Perception viewed as an inverse problem (Pizlo 2000)
Stabilized images on the retina (Pritchard 1961)
Optional, extra resources:
Multiple Worlds (Koenderink 2012)
Experimental Phenomenology: Art and Science (Koenderink 2012)
Module 2 Early visual processing
Readings: Receptive Fields Primer (Lennie 2003)
Theory of Edge Detection (Marr and Hildreth, 1980)
What Line Drawings Reveal about the Visual Brain (Sayim and Cavanagh, 2011)
Pictorial Space (Koenderink 2012)
The Generic Viewpoint Assuption and Illusory Contours
Optional, extra resources:
Selections from Suprematism Manifesto (Malevich 1924)
White Manifesto (Fontana 1946)
Lumia: Thomas Wilfred and the Art of Light (2017)
Vision in Motion (Moholy-Nagy 1947)
Language of Vision (Kepes 1951)
On the Purity of Light (Piene 1958) from Zero, MIT Press
My Position in the Battle Between Line and Color (Klein 1958)
Art and the Limits of Neuroscience (from Alva Noe, Strange Tools and Human Nature, 2015)
Module 3 Binocular vision, depth, and motion perception
Readings: Perceived Lightness Depends on Perceived Spatial Arrangement (Gilchrist 1977)
Role of Learning in Three-dimensional Form Perception (Sinha and Poggio 1996)
Sinha Slides: Stereo/motion/lightness
Optional, extra readings:
Perception and Reality: Why a Wholly Empirical Paradigm is Needed to Understand Vision (Purves et al. 2015)
Selection from James Turrell: A Retrospective (Holzherr 2013)
Selection from More Light artists (Lipp, Zec 1985)
Gauge Fields in Pictorial Space (Koenderink and Van Doorn 2012)
Why we see things the way we do (Purves et al. 2001)
https://docs.google.com/presentation/d/1UKGOls6ubW5YIEeLflCTjfeELFQJR1ns/edit?usp=drive_link&ouid=112934696816129912997&rtpof=true&sd=truePawan SInha: Stereo, Motion, Light
Module 4 Color and Light
Readings: #TheDress: Categorical Perception of an Ambiguous Color Image (Lafer-Sousa and Conway, 2017)
Seeing in Color (Lotto et al 2011)
Optional, extra readings:
Color Appearance and the End of Herring’s Opponent-Colors Theory (Conway et al., 2023)
Sensory, Computational and Cognitive Components of Human Color Constancy (Smithson 2005)
Excerpt from Interaction of Color (Albers)
Perception of Three-Dimensional Shape Influences Colour Perception through Mutual Illumination (Bloj et al. 1999)
Presentations:
Brandon Jackson: Constructing Reprsentations of Colour
Module 5 Recognition, compositionality, and perceptual primitives
Readings: Seeing Faces is Necessary for Face Domain Formation (Arcaro et al. 2017)
Bayesian Models of Object Perception (Kersten and Yuille 2003)
Guest speaker reading: Perceptual Plausibility of Exaggerated Realistic Motion (Schmidt et al 2024)
Optional, extra readings:
Paul Cézanne: The Process of Sight (Lehrer, excerpt from Proust Was A Neuroscientist)
“Top-Down” Effects Where None Should Be Found (Firestone 2013) Optional, extra readings:
Module 6 Art and associative recall
On the Perception of Probable Things: Neural Substrates of Memory, Learning, and Perception (Albright 2012)
Optional, extra readings:
Words Jump-Start Vision (Boutonnet and Lupyan 2015)
Associative Learning Mechanisms in Vision, excerpt Visual Memory (eds. Luck/Hollingworth 2008)
Presentations:
Pawan Sinha: Art and Associative Recall
Pawan SInha; Molyneux
Instructors
Pawan Sinha
Pawan Sinha is a professor of vision and computational neuroscience in the Department of Brain and Cognitive Sciences at MIT. He received his undergraduate degree in computer science from the Indian Institute of Technology, New Delhi and his Masters and doctoral degrees from the Department of Computer Science at MIT. Using a combination of experimental and computational modeling techniques, research in Pawan’s laboratory focuses on understanding how the human brain learns to recognize objects through visual experience and how objects are encoded in memory. The lab’s experimental work on these issues involves studying healthy individuals and also those with neurological disorders such as autism. A key initiative of the lab is Project Prakash; this effort seeks to accomplish the twin goals of providing treatment to children with disabilities and also understanding mechanisms of learning and plasticity in the brain.
contact: psinha AT mit.edu
Seth Riskin
Seth Riskin runs the MIT Museum Studio and Compton Gallery, a space for interdisciplinary projects and experimental exhibitions. He also oversees the Holography and Spatial Imaging area at the MIT Museum. A light artist who conducts humanistic research of light across disciplines and cultures, Seth brings to the course hands-on methods for controlling light and shaping the visual perception of form, space and time, as well as expertise in the values and meanings of light and how they contribute to what we see.
contact: riskin AT mit.edu
Sarah Schwettmann
Sarah Schwettmann is a computational neuroscientist interested in creativity underlying the human relationship to world: from the brain’s fundamentally constructive role in sensory perception to the explicit creation of experiential worlds in art. She is a research scientist with the Vision group in MIT CSAIL and MIT-IBM Watson AI Lab. She received her PhD from MIT’s Department of Brain and Cognitive Sciences, where she was an NSF Graduate Research Fellow. Previously, Sarah was also a member of the Eagleman Laboratory for Perception and Action at Baylor College of Medicine and the Shouval Lab for Theoretical Neuroscience at UT Health Science Center Houston. In the arts, Sarah uses her background in computation to create installations that explore structure in human cognition and the nature of intelligence. Her work has been exhibited at FiftyThree in New York and at OPEN Gallery in Boston. Sarah received BAs in Computational and Applied Mathematics and Cognitive Science from Rice University, where she was a Trustee Distinguished Scholar, Century Scholar, and taught courses on Engineering Computation and Women Leaders in STEM.
contact: schwett AT mit.edu
@cogconfluence