Studies of the visual system are taking large steps toward a general understanding of how sensory neurons are wired to encode the outside world. A visual scene is first processed by the retina and thalamus for reliable identification of basic features across a broad range of natural conditions, an impressive feat that requires a complex network. From there, visual information propagates through multiple stages of cortex to build up a neural representation that is more in-tuned with complex features of the natural world. However, we are missing the basic physiological principles underling this visual hierarchy. Footing for this problem may reside in the finding that basic anatomical architecture is repeated within the neocortex, which implies that discoveries in each visual cortical area have broad implications for normal visual perception, along with cortical-based pathologies. Our lab uses novel imaging and genetic tools to probe the mechanisms of a single cortico-cortical processing stage: V1-to-V2. Cortical area V2 receives the majority of its input from cortical area V1, where many labs, such as ours, have been fruitful at characterizing responses to simple visual stimuli. Taken together, V2 provides a strong handle to understand cortical processing since its responses can be interpreted as computations on a fairly well characterized set of inputs, V1. The goal of this two-year project is to determine if visual computations in V2 are segregated across its surface to form a ?computational map?, which would provide major experimental leverage to study the underlying mechanisms. This hypothesis is supported by previous studies showing that V2 compartments have unique functional signatures, albeit not ?computational?, in that they are simply inherited from V1. Testing for a computational map will be done in a novel experimental preparation: We will simultaneously image V1 and V2 activity with calcium imaging, which will allow for a rigorous assessment of V1-to-V2 transformations at each cortical location, with cellular resolution. Our lab is uniquely suited to accomplish the necessary combination of high-resolution imaging and quantitative analysis.
Aim 1 will test how linear receptive fields in V1 tile the visual scene, which is necessary to understand coding limitations of the V1 population, along with interpretations of how V1 is affecting its downstream target, V2. Next, Aim 2 will directly test for V1-to-V2 computations by comparing V1 and V2 responses to more complex visual stimuli, consisting of the superposition of multiple stimulus elements. Our innovative approach has the potential to answer major scientific questions, while also laying important groundwork to further investigate the details of V1-to-V2 circuitry - Future experiments will use advanced genetic tools to test hypotheses about the specific physiological mechanisms giving rise to cortical computation. A physiological model of human perception and behavior will ultimately require testing of basic cortico-cortical computations in the primate, such as the transformations between V1 and V2 studied here.

Public Health Relevance

Modeling the mechanisms by which visual cortical neurons integrate inputs to produce outputs is necessary to obtain a mechanistic understanding of visual processing and also contributes more generally to understanding circuit mechanisms across all of the cerebral cortex. Deficits in central visual processing are linked to dyslexia, strabismus, and amblyopia. Furthermore, the mechanisms uncovered in visual cortex are likely to reveal general processing strategies for other cortical areas, thus having important implications for diseases such as schizophrenia and autism, where cortical-based pathologies are linked. !

Agency
National Institute of Health (NIH)
Institute
National Eye Institute (NEI)
Type
Exploratory/Developmental Grants (R21)
Project #
1R21EY029849-01
Application #
9651549
Study Section
Mechanisms of Sensory, Perceptual, and Cognitive Processes Study Section (SPC)
Program Officer
Flanders, Martha C
Project Start
2019-02-01
Project End
2021-01-31
Budget Start
2019-02-01
Budget End
2020-01-31
Support Year
1
Fiscal Year
2019
Total Cost
Indirect Cost
Name
University of Texas Austin
Department
Psychology
Type
Schools of Arts and Sciences
DUNS #
170230239
City
Austin
State
TX
Country
United States
Zip Code
78759