The Systems neurobiology Laboratory is a group of laboratories that all study various aspects of neurobiology. These laboratories include: (1) computational neurobiology Laboratory: The goal of their research is to build bridges between brain levels from the biophysical properties of synapses to the function of neural systems. (2) computational Principles of Natural Sensory Processing: Research in this lab focuses on the computational principles of how the brain processes information. (3) Laboratory for Cognitive neuroscience: This laboratory studies the neural and genetic underpinnings of language and cognition. (4) Sloan-Swartz Center for Theoretical neurobiology: The goal of this laboratory is develop a theoretical infrastructure for modern experimental neurobiology. (5) Organization and development of visual cortex: This laboratory is studying the organization and function of neural circuits in the visual cortex to understand how specific neural components enable visual perception and to elucidate the basic neural mechanisms that underlie cortical function. (6) Neural mechanism of selective visual attention: This laboratory studies the neural mechanisms of selective visual attention at the level of the individual neuron and cortical circuit, and relates these findings to perception and conscious awareness. (7) Neural basis of vision: This laboratory studies how sensory signals in the brain become integrated to form neuronal representation of the objects that people see.

Our mission is to reveal the molecular logic of our intelligence in health and disease. We use advanced molecular biological tools and state-of-the-art neuroscience to test the role of synaptic and neuronal molecules in the dynamics of the living brain.

Artificial neural networks have been heavily inspired by the brain’s architecture, guiding our journey to discovering the keys to intelligence. We now find ourselves at a pivotal moment: today's AI systems surpass biological circuits in certain tasks, yet we still lack a fundamental understanding of the mechanisms behind the brain’s superior cognitive flexibility and efficiency. At Ingie Hong’s Quantitative Intelligence Lab, we are dedicated to unraveling the principles that enable the mammalian cortex to achieve remarkable feats of intelligence, including rapid learning, generalization, and inference across vast stores of memory.

A single neuron’s response depends on its synaptic connections and intrinsic properties, which are dictated by the expression of neuronal genes. However, the role of these molecules in brain computations remains largely uncharted territory. Focusing on the mouse visual cortex as a starting point for broader generalization, and using large-scale electrophysiology, advanced microscopy, and machine learning, we have begun to uncover the impact of key synaptic genes on cortical processing and their role in the brain’s “working algorithm” (Hong et al., Nature, 2024). Our molecular tools, including gene therapy vectors and antisense oligonucleotides, show promise as effective therapeutic candidates.

Our research will advance the nascent field of 'neurocomputational therapeutics'—innovative genetic and pharmacological tools that address biases in neural activity. These tools will not only facilitate the development of novel mechanism-based treatments for brain disorders but also inspire the next generation of intelligent artificial neural networks.