The overall goal of the proposed research is to provide a quantitative understanding of the link between neural activity in the primate primary visual cortex (V1) and behavioral performance in visual detection and discrimination tasks. To achieve this goal, monkeys are trained to perform four demanding visual detection and discrimination tasks using small oriented visual stimuli that could appear in isolation or on top of a visual mask. While the monkey performs these tasks, we use voltage-sensitive dye optical imaging in conjunction with electrophysiology, to monitor neural population activity in V1. We then use computational techniques to study the relationships between the visual stimuli, the measured neural responses at multiple spatial scales, and the observed behavioral responses to these stimuli. Our first two aims focus on two fundamental causal relationships between these three variables.
In Aim #1 our goal is to determine how visual information regarding the target and the mask is represented, or encoded, by populations of V1 neurons. We address three primary questions: (i) what is the quality of the signals that are provided to the rest of the visual system by V1 responses at multiple spatial scales, (ii) how is this information distributed in V1, and (iii) what is the optimal way to extract this information from V1? To form a decision regarding the target, neural circuits subsequent to V1 must 'read out', or decode, the neural signals provided by populations of V1 neurons. Our goal in Aim #2 is to determine which neurons in V1 contribute to the perceptual decision regarding the target, and how their signals might be pooled to form this decision. Finally, these two fundamental relationships - the encoding of visual information by V1 neurons, and the decoding of V1 responses by subsequent processing stages - may change, depending on the behavioral task.
In Aim #3, we vary the task by modulating target uncertainty and target relevance. We then examine if and how top-down mechanisms change the representation of the target in V1 based on the demands of the task. Together, this research will significantly expand our understanding of the way in which information is represented and processed by populations of neurons in the primate cortex.
Our ability to perceive, recognize, and act upon objects in our environment is mediated by neural circuits in the cerebral cortex. Our long-term goal is to understand how neural circuits in the cerebral cortex represent and process visual information. By addressing this goal, our research will help to elucidate the normal function of the cerebral cortex and its malfunction in neurological and neuropsychiatric disease.
|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|
|Sit, Yiu Fai; Chen, Yuzhi; Geisler, Wilson S et al. (2009) Complex dynamics of V1 population responses explained by a simple gain-control model. Neuron 64:943-56|
|Chen, Yuzhi; Geisler, Wilson S; Seidemann, Eyal (2008) Optimal temporal decoding of neural population responses in a reaction-time visual detection task. J Neurophysiol 99:1366-79|
|Palmer, Chris; Cheng, Shao-Ying; Seidemann, Eyal (2007) Linking neuronal and behavioral performance in a reaction-time visual detection task. J Neurosci 27:8122-37|
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