Experience-dependent plasticity is a prominent feature of the sensory cortices and occurs throughout one's lifetime by a variety of sensory experiences. Investigating the neural mechanisms of perceptual learning will enhance our understanding of plasticity in the adult brain and provide novel insights into learning disabilitie. Although the functional advantage is obvious, precisely what kinds of neural changes lead to improved perception is still under debate. The proposed career development plan aims to gain fundamental insights into the neural network-level mechanisms of visual perceptual learning, while establishing an independent academic career in a university setting. The candidate has considerable experience studying cortical function in awake behaving mice monitoring patterned activity in hundreds of neurons simultaneously using advanced optical techniques. She now proposes to undergo new training in rodent behavior and cutting-edge optical stimulation tools, to reach her long-term goal of becoming an independent scientist studying network-level plasticity in the adult cortex in healthy and diseased states. She will carry out the mentored phase under the guidance of Dr. Rafael Yuste, a world expert in developing optical methods and applying them to investigation of the structure and function of cortical microcircuit. Using two-photon calcium imaging to measure network activity from hundreds of neurons simultaneously in the primary visual cortex of awake mice, the candidate recently discovered that specific visual stimuli evoke distinct sets of neuronal ensembles and these ensembles respond far more reliably to visual stimuli than individual neurons. Furthermore, the same neuronal ensembles are activated spontaneously and in response to visual stimulation, suggesting that the cortical representation of visual attributes is built out of intrinsic activity patterns. The candidate now proposes to apply novel optical imaging and manipulation techniques to understand the mechanisms of how network-level activity is modified by sensory experience. During the mentored phase, she will use fast imaging and optogenetic techniques to understand the circuit mechanisms of perceptual learning during visual stimulation as well as during spontaneous activity following a perceptual learning task. In the independent phase of the award the candidate will use these newly acquired technical skills to determine the distinct roles of basal forebrain cholinergic and GABAergic inputs to V1 ensemble activity during perceptual learning. Training in novel optical methods and rodent behavior as outlined in the research plan will equip the candidate to embark on a comprehensive and fruitful research program as an independent researcher. The proposed studies will become a foundation for future studies on adult plasticity in other sensory modalities and will provide novel insights into how learned information is encoded throughout the cerebral cortex.
The cerebral cortex is the largest part of the mammalian brain and the primary site for our perception, memory, language, and imagination, yet its circuits are still quite mysterious. The proposed project will investigate the experience-dependent plasticity in adult cortical circuit at the network level. The findings from this work will significantly contribute to our knowledge of plasticity in the adult brain and to generating novel strategies for the rehabilitation of skills in individuals with neurological deficits.
|Karimipanah, Yahya; Ma, Zhengyu; Miller, Jae-Eun Kang et al. (2017) Neocortical activity is stimulus- and scale-invariant. PLoS One 12:e0177396|
|Carrillo-Reid, Luis; Yang, Weijian; Kang Miller, Jae-Eun et al. (2017) Imaging and Optically Manipulating Neuronal Ensembles. Annu Rev Biophys 46:271-293|
|Carrillo-Reid, Luis; Miller, Jae-Eun Kang; Hamm, Jordan P et al. (2015) Endogenous sequential cortical activity evoked by visual stimuli. J Neurosci 35:8813-28|
|Miller, Jae-eun Kang; Ayzenshtat, Inbal; Carrillo-Reid, Luis et al. (2014) Visual stimuli recruit intrinsically generated cortical ensembles. Proc Natl Acad Sci U S A 111:E4053-61|