# Predictive Functions and Neural Mechanisms of Spontaneous Cortical Activity

> **NIH NIH K08** · STANFORD UNIVERSITY · 2024 · $194,076

## Abstract

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 ta...

## Key facts

- **NIH application ID:** 10818580
- **Project number:** 5K08MH131888-02
- **Recipient organization:** STANFORD UNIVERSITY
- **Principal Investigator:** Anish Mitra
- **Activity code:** K08 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $194,076
- **Award type:** 5
- **Project period:** 2023-05-01 → 2027-04-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10818580

## Citation

> US National Institutes of Health, RePORTER application 10818580, Predictive Functions and Neural Mechanisms of Spontaneous Cortical Activity (5K08MH131888-02). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10818580. Licensed CC0.

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