Acute pain is an early-warning physiological signal triggered in the nervous system, essential for survival. However, pain processing is fragile as inflammation, injury, and malfunction of the nervous system may divert its function, creating a debilitating disease known as chronic pain (CP). CP affects 100 million adults in the US and is primarily treated with drugs, which may be inadequate or toxic, have negative side effects (e.g., addiction to narcotics), and lose efficacy over time. Electrical stimulation to targeted nerve fibers is an alternative therapy that has great potential with less negative side effects but has had suboptimal efficacy and limited long-term success, as its mechanisms of action are unclear.

Critical to advancing CP treatment is a deeper mechanistic understanding of pain transmission under normal and pathological conditions, which remains elusive because the pain system is complex. When a splinter pricks your toe, it stimulates a nerve fiber. A pain sensor called a nociceptor sends an electrical impulse up your leg to a cluster of cells in the spinal cord called the dorsal horn (DH). There, the nerve impulse is processed by neurons and sent up to the thalamus in the brain, which relays the information that your toe has been pricked to the somatosensory cortex (which senses it), frontal cortex (which thinks about it), and limbic system (which reacts to it emotionally). These simple processing steps don’t even hint at the baffling complexity of pain. For example, make the injury worse—a broken toe. The fracture hurts because tissues and nerves around the damaged bone have suffered trauma. Eight weeks later, the bone and nerves have mended but the pain persists. Why?

This is an open question because the pain system is difficult to probe—experimental barriers—and difficult to analyze—computational barriers. The DH is the pain processing center and contains inhibitory, excitatory, and projections neurons. Electrophysiological recordings of these neurons, therefore, provide important dynamic information about changes in their responses to disease, injury, or treatment for CP. Yet, it is difficult to differentiate subsets of DH neurons and simultaneously study their physiological properties. Tracing and staining of injected dye is complicated, inefficient, and the neuron’s neurochemical identity is unknown prior to recording.

A complement to biological experiments is realistic mathematical models of the DH circuit. Although current models reproduce some observed behaviors, they assume a fixed circuit topology, are high dimensional and nonlinear. Therefore, it is not tractable to analytically characterize the set of sensory stimuli and parameters (including treatment parameters) that result in firing patterns related to pain. If we can quantify how model parameters impact the firing of DH neurons, then we can “steer” the dynamics into normal ranges with therapy.

We are working on constructing a tractable computational model of the DH circuit consistent with experimental data to analyze and test how different sensory stimuli and therapies modulate pain perception. Through our collaborations with Dr. Yun Guan (JHH), we are generating novel data using state-of-the-art electrophysiological techniques and powerful mouse genetic approaches will delineate the effects of sensory stimuli and stimulation on various subsets of DH neurons. These data will then be used to estimate parameters and circuit topology of a detailed mechanistic model of the DH. Nonlinear control systems techniques will be applied to the detailed model to generate a tractable characterization of the DH enabling sensitivity analysis. Finally, model predictions will be tested experimentally.


This work is done in collaboration with:

  • Yun Guan (Johns Hopkins Hospital)
  • Stan Anderson (Johns Hopkins Hospital)