Visual Coding and Cortical Plasticity: From Synapse to Perception
Summary: Yang Dan's laboratory studies how visual information is processed by cortical circuits and how circuit dynamics vary across brain states. Using both bottom-up and top-down approaches and a combination of electrophysiology, imaging, and computational techniques, her group aims to understand neural processing at multiple levels, from single synapses to cortical microcircuitry, and from network dynamics to animal behavior.
The long-term goals of our research are (1) to decipher the neural code in the mammalian visual system and to dissect the underlying neuronal circuitry; (2) to characterize how cortical circuits are modified by sensory experience, and how these modifications contribute to learning and memory; and (3) to understand how cortical network dynamics are controlled by brain states and the neuromodulatory systems. We use a multidisciplinary approach, combining advanced computational analyses and experimental investigations that involve a broad spectrum of techniques.
Neural processing occurs at multiple levels—from subcellular dendritic compartments to local circuits of interconnected neurons, to large ensembles over extended brain areas. Although the traditional approach of studying each level in isolation has been fruitful in previous decades, some of the artificial divides have begun to hinder our progress. A key feature of our research program is the integration of studies at multiple organizational levels of the nervous system—from synapse, to network, to behavior. Our expertise in computational analyses plays an important role in bridging our experimental studies at different levels.
Microcircuitry, Receptive Field, and Plasticity in the Visual Cortex
An essential step in understanding sensory processing is to elucidate the intricate synaptic circuitry underlying the neural representation of various sensory features. Among all sensory cortical areas, the primary visual cortex (V1) is the best understood regarding the neuronal receptive field properties. Thus it provides a unique opportunity for investigating the underlying circuitry.
Previous studies of cortical microcircuitry have focused mainly on its physical structure, defining the rules of connectivity in terms of laminar location and neuronal morphology. However, in building models of cortical circuitry underlying the receptive field properties, it becomes clear that the rules of connectivity must also be specified in terms of the functional properties of the pre- and postsynaptic neurons. Our strategy for studying cortical circuitry and plasticity is to emphasize the neuronal response properties and to analyze synaptic connectivity with respect to the visual feature selectivity of each neuron in the circuit. We are currently combining in vivo two-photon Ca2+ imaging and intracellular (whole-cell) recording with computational analysis of cortical receptive fields. In collaboration with other researchers, we are also using optogenetic techniques to manipulate the activity of specific cell types and to test their contributions to visual cortical receptive field properties.
Population Neural Dynamics in Visual Coding and Memory Storage
In addition to the microcircuitry within cortical columns that gives rise to the basic receptive field properties, there are also extensive horizontal connections between columns, which mediate distinct functions. These horizontal connections are highly susceptible to activity-dependent synaptic modifications, and they play important roles in both developmental circuit refinement and adult learning and memory. Due to their broad spatial distributions, the horizontal connections can coordinate the activity of large neuronal populations and mediate long-range perceptual interactions between different parts of the visual scene. To study visual coding and plasticity at the neuronal ensemble level, we have established multielectrode recording and voltage-sensitive dye-imaging techniques to analyze large-scale spatiotemporal activity patterns.
Our experiments have revealed a prevalence of spontaneous and visually evoked activity waves propagating over large areas of the adult visual cortex in both anesthetized and awake animals, presumably mediated by horizontal connections. Intriguingly, visually evoked activity patterns appear to reverberate in subsequent spontaneous waves. These initial observations have led us to investigate the interactions between visual experience and spontaneous cortical waves in visual processing and perceptual learning. Mechanistically, the reverberation may result from activity-dependent plasticity of horizontal connections. Functionally, such reverberation of recent sensory experience may play important roles in memory consolidation. We are using a combination of voltage-sensitive dye imaging and multielectrode recording to test these hypotheses.
Neural Modulation and Brain States
Different behavioral states of the animal (e.g., asleep/awake, drowsy/aroused) are known to be associated with distinct global patterns of brain activity. Although previous studies have revealed a number of neuromodulatory systems involved in regulating brain states, it remains unclear how each system modulates neuronal circuit dynamics, how the multitude of neuromodulatory systems interact with each other, and what functional roles are served by each brain state.
In a recent study, we have shown that activation of the basal forebrain cholinergic system can cause a marked desynchronization between cortical neurons and improvement in the reliability of neuronal responses to visual stimuli. We are currently using a combination of optogenetics, imaging, and electrophysiology to address the following questions: (1) How do activation and inactivation of the cholinergic neurons in awake animals affect their visual processing and behavior? (2) What are the roles of specific neuronal types (e.g., interneurons expressing distinct molecular markers) in mediating the cholinergic modulation of cortical dynamics? (3) Is the effective connectivity in cortical circuits modulated by cholinergic input and behavioral state? (4) How are the activity patterns of cholinergic neurons related to the natural behaviors of the animal and to the activity of other modulatory neurons (e.g., dopaminergic neurons)? We believe that this line of research provides fertile ground for understanding the neural basis of behavior.
This laboratory is supported in part by the National Institutes of Health and the National Science Foundation.
As of January 14, 2009