The Mark Dredze Lab investigates topics such as natural language processing, speech, machine learning and intelligent user interfaces. Our team is currently exploring several key health information applications, including information extraction from social media and biomedical and clinical texts. Our recent research in these areas include vaccine communication during the Disneyland measles outbreak; the validity of online drug forums for estimating trends in drug use; and the use of Twitter to examine social rationales for vaccine refusal.

The Suchi Saria Lab, part of the Institute for Computational Medicine, explores topics within the fields of machine learning and computational statistics, with a focus on computational solutions for problems in health informatics. Our team investigates the applications of machine learning and computational statistics to domains where one has to draw inferences from observing a complex, real-world system evolve over time. We use Bayesian and probabilistic graphical modeling approaches to address the challenges that emerge with modeling and prediction in real-world temporal systems.

The Paul Worley Lab examines the molecular basis of learning and memory. In particular, we cloned a set of immediate early genes (IEGs) that are rapidly transcribed in neurons involved in information processing, and that are essential for long term memory. IEG proteins can directly modify synapses and provide insight into cellular mechanisms that support synapse-specific plasticity.

The David Linden Laboratory has used both electrode and optical recording in cerebellar slice and culture model systems to explore the molecular requirements for induction and expression of these phenomena. Along the way, we discovered a new form of plasticity. In addition, we have expanded our analysis to include use-dependent synaptic and non-synaptic plasticity in the cerebellar output structure, the deep nuclei. Our investigations are central to understanding the cellular substrates of information storage in a brain area where the behavioral relevance of the inputs and outputs is unusually well defined. In addition, our investigations have potential clinical relevance for cerebellar motor disorders and for disorders of learning and memory generally.

The goals of the Vikram Chib Lab are to understand how the nervous system organizes the control of movement and how incentives motivate our behaviors. To better understand neurobiological control, our researchers are seeking to understand how motivational cues drive our motor actions. We use an interdisciplinary approach that combines robotics with the fields of neuroscience and economics to examine neuroeconomics and decision making, motion and force control, haptics and motor learning, image-guided surgery and soft-tissue mechanics.

Directed by Debraj “Raj” Mukherjee, MD, MPH, the laboratory focuses on improving access to care, reducing disparities, maximizing surgical outcomes, and optimizing quality of life for patients with brain and skull base tumors.

The laboratory achieves these aims by creating and analyzing institutional and national databases, developing and validating novel patient-centered quality of life instruments, leveraging machine learning and artificial intelligence platforms to risk-stratify vulnerable patient populations, and designing novel surgical trials to push the boundaries of neurosurgical innovation.

Our research also investigates novel approaches to improve neurosurgical medical education including studying the utility of video-based surgical coaching and the design of new operative instrumentation.

Our team is focused on understanding how complex movements are normally learned and controlled, and how damage to specific brain areas impairs these processes. We employ several techniques to quantify movement including: 3-dimensional tracking and reconstruction of movement, recordings of muscle activity, force plate recordings, and calculation of joint forces and torques. These techniques allow for very precise measurements of many different types of movements including: walking, reaching, leg movements, hand movements and standing balance. All studies are designed to test specific hypotheses about the function of different brain areas, the cause of specific impairments and/or the effects of different interventions.

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.

Our research is directed toward how the brain controls the movements of the eyes (including eye movements induced by head motion) using studies in normal human beings, patients and experimental animals. The focus is on mechanisms underlying adaptive ocular motor control. More specifically, what are mechanisms by which the brain learns to cope with the changes associated with normal development and aging as well as the damage associated with disease and trauma? How does the brain keep its eye movement reflexes properly calibrated? Our research strategy is to make accurate, quantitative measures of eye movements in response to precisely controlled stimuli and then use the analytical techniques of the control systems engineer to interpret the findings. Research areas: 1) learning and compensation for vestibular disturbances that occur either within the labyrinth or more centrally within the brain, 2) the mechanisms by which the brain maintains correct alignment of the eyes to prevent diplopia and strabismus, and 3) the role of ocular proprioception in localizing objects in space for accurate eye-hand coordination.

A basic and translational science laboratory focused on diseases of platelets. We are interested in learning the physiologic mechanisms of platelet function, characterizing the genetic variants that can cause inherited platelet dysfunction, and developing therapeutics that can modulate platelet function to ameliorate human disease.