The overarching goal of the current proposal is to uncover the neural mechanisms that underlie figure-ground segregation, an important component of natural scene interpretation, focusing on the role of the primary visual cortex (V1) and its dynamic interactions with higher visual cortical areas. Specifically, we will measure how V1 responds to a wide range of backgrounds, including artificial and naturalistic textures, with and without occluding targets, and develop computational encoding models that would allow one to predict V1 population responses at multiple biologically-relevant spatial scales to arbitrary figures and backgrounds (Aim 1).
In Aim 2 we will study the role of V1 in figure-ground discrimination by measuring and perturbing V1 population responses while animals detect a camouflaged target that occludes a background of the same texture family. These experiments will be used to distinguish between different candidate decoding models that describe how single-trial V1 population responses lead to behavior in the task. An important goal would be to test whether V1 plays an active role in the segmentation computation. The alternative is that V1 provides the feedforward input to a segmentation computation that occurs downstream, and receives top-down figure-ground signals only after the segmentation had been completed. Overall, the proposed experiments will lead to a deeper understanding of the role of V1 in fundamental mid-level visual computations and will serve as an important step toward a quantitative understanding of the representation of complex natural scenes by populations of neurons in V1.

Public Health Relevance

The overarching goal of the proposed research is to uncover the role of the primate primary visual cortex (V1) in mediating figure-ground segmentation. We will use multiple experimental techniques to monitor and manipulate neural responses in V1 while animals perform a demanding figure-ground discrimination task with camouflaged targets. These experiments will allow us to test specific hypotheses regarding the way in which V1 interacts with downstream circuits to mediate figure-ground discrimination.

National Institute of Health (NIH)
National Eye Institute (NEI)
Research Project (R01)
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Mechanisms of Sensory, Perceptual, and Cognitive Processes Study Section (SPC)
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Flanders, Martha C
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University of Texas Austin
Schools of Arts and Sciences
United States
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Seidemann, Eyal; Geisler, Wilson S (2018) Linking V1 Activity to Behavior. Annu Rev Vis Sci 4:287-310
Benvenuti, Giacomo; Chen, Yuzhi; Ramakrishnan, Charu et al. (2018) Scale-Invariant Visual Capabilities Explained by Topographic Representations of Luminance and Texture in Primate V1. Neuron 100:1504-1512.e4
Michel, Melchi M; Chen, Yuzhi; Seidemann, Eyal et al. (2018) Nonlinear Lateral Interactions in V1 Population Responses Explained by a Contrast Gain Control Model. J Neurosci 38:10069-10079
Seidemann, Eyal; Chen, Yuzhi; Bai, Yoon et al. (2016) Calcium imaging with genetically encoded indicators in behaving primates. Elife 5:
Yang, Zhiyong; Heeger, David J; Blake, Randolph et al. (2015) Long-range traveling waves of activity triggered by local dichoptic stimulation in V1 of behaving monkeys. J Neurophysiol 113:277-94
Tan, Andrew Y Y; Chen, Yuzhi; Scholl, Benjamin et al. (2014) Sensory stimulation shifts visual cortex from synchronous to asynchronous states. Nature 509:226-9
Michel, Melchi M; Chen, Yuzhi; Geisler, Wilson S et al. (2013) An illusion predicted by V1 population activity implicates cortical topography in shape perception. Nat Neurosci 16:1477-83
Chen, Yuzhi; Palmer, Chris R; Seidemann, Eyal (2012) The relationship between voltage-sensitive dye imaging signals and spiking activity of neural populations in primate V1. J Neurophysiol 107:3281-95
Palmer, Chris R; Chen, Yuzhi; Seidemann, Eyal (2012) Uniform spatial spread of population activity in primate parafoveal V1. J Neurophysiol 107:1857-67
Chen, Yuzhi; Seidemann, Eyal (2012) Attentional modulations related to spatial gating but not to allocation of limited resources in primate V1. Neuron 74:557-66

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