Predictive Functions and Neural Mechanisms of Spontaneous Cortical Activity

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The mammalian cortex is spontaneously active even in the absence of external stimuli. Initially dismissed as neural noise, pioneering work established that the internal brain states produced by spontaneous activity are highly structured and responsible for the dramatic variability in both neural and perceptual responses to the same sensory stimulus. The discovery that varying spontaneous cortical states (SCS) drive different responses to identical stimuli suggested that altered perceptions of the environment across psychiatry could derive from aberrant SCS. On this basis, ongoing resting state fMRI studies continue to search for reproducible links between SCS and psychiatric diagnoses, including schizophrenia, depression, and PTSD, among others. Yet our fundamental understanding of the cognitive processes and circuit mechanisms underlying SCS remains limited. One leading theory, drawn from human fMRI recordings during visual detection tasks, suggests that SCS represent predictions about the environment. In this model, predictive spontaneous cortical states influence perceptual decision making on the basis of prior beliefs. However, several critical gaps remain in this theory. At present, there is no causal evidence, either through closed-loop behavior or direct neural modulation, linking SCS to perceptual decisions. Moreover, the circuit mechanisms of SCS, including the role of interneurons in producing SCS and specific cortical areas in driving spontaneous cortex-wide states, are completely unknown. My proposal aims to address these knowledge gaps by investigating SCS in a mouse model. Having trained mice in a two-alternative forced choice visual detection task, I have applied optical imaging of the dorsal cortex to find that specific spontaneous states predict behavioral response. Leveraging my preliminary data, I will investigate how specific interneuron types contribute to SCS (Aim 1), test the causal influence of predictive SCS over perceptual decisions through a closed-loop behavior (Aim 2), and apply optogenetic modulation of neural activity to test the role of a specific cortical area, the retrosplenial cortex, in driving predictive SCS (Aim 3). The proposed studies will offer novel insights into the neurocognitive mechanisms underlying spontaneous activity, including in human resting state fMRI. In the process, I will supplement my background in human resting state neuroimaging with critical training in rodent behavior, psychophysics methods, and optogenetics. My proposal will be guided by a world-class advisory committee consisting of my primary mentor Dr. Karl Deisseroth, an expert in optogenetics and animal behavior, Dr. Michael Stryker, a mouse visual system expert, Dr. Brian Wandell, an expert in perceptual decision making, Dr. Robert Malenka, a rodent nervous system expert, and Dr. Nolan Williams, an expert in human neuromodulation. I will further take full advantage of the vibrant training environment at Stanford by engaging in targeted coursework and high-quality professional development. By the end of the fellowship, I will be positioned to launch a career as an independent investigator studying how the neurocognitive processes embedded in spontaneous activity contribute to psychiatric illness.