The Joanne Shay Lab primarily conducts research on pediatric pain management techniques. Our studies have explored pain management in special-needs children and patients, and we have studied non-traditional pain management methods, such as regional anesthesia and peripheral nerve blocks in children, medical acupuncture, and remote anesthesia services. We also have an ongoing interest in the business of medicine.

The Daniel Weinberger Laboratory focuses on the neurobiological mechanisms of genetic risk for developmental brain disorders. We study the genetic regulation of the transcriptome in normal human brain across the human life span and in brains from patients with various psychiatric disorders. We also study the impact of genetic variation on aspects of human brain development and function linked with risk for schizophrenia and related psychiatric disorders. Our lab uses unique molecular and clinical datasets and biological materials from a large sample of families with affected and unaffected offspring and normal volunteers. These datasets include DNA, lymphoblast and fibroblast cell lines, and extensive quantitative phenotypes related to genetic risk for schizophrenia, including detailed cognitive assessments and various neuroimaging assays. In other research, we are working on a human brain transcriptome project that is RNA sequencing over 1,000 human brain samples in various regions and based also on sorting of specific celliular phentypes. We are exploring the molecular processing of the gene and its implications for cognition and aspects of human temperament.

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.