Medical interventions often come about by the application of current theory surrounding a disease, but ultimately whether one is approved and used in patients depends not on whether it fits with current dogma, but simply on whether it works. Consequently, as the theories surrounding how a disease develops change with new research, studying why certain treatments are effective can provide further information about the disease’s pathophysiology. In addition, research into how a treatment exerts its effect can reveal avenues to refine and improve the intervention, as well as generate new and better strategies to tease apart and understand complex biological systems.

Dr. Viviana Gradinaru’s lab at Caltech uses new techniques in neuroscience such as optogenetics, CLARITY, and 2-photon imaging to study deep brain stimulation (DBS), which is an effective treatment for various neurological disorders. As a postdoctoral researcher working with Dr. Karl Deisseroth at Stanford, Dr. Gradinaru used the then-developing technique of optogenetics to study how DBS of the subthalamic nucleus (STN) improves the symptoms of Parkinson’s disease. Optogenetics is a technique where light-activated channels are expressed in neurons and used to influence the behavior of those neurons. These channels can also be targeted to specific populations of neurons using those neurons’ genetic markers, making this technique especially powerful.

The researchers used optogenetics to attempt to identify which populations of cells contribute to the efficacy of DBS in the STN. First, they created mice that model Parkinsonian symptoms by using a chemical called 6-OHDA to kill most of the dopamine neurons in the substantia nigra pars compacta (neurons which are lost in Parkinson’s disease). Unlike in Parkinson’s disease, however, the neurons were killed only on one side of the brain, causing deficits only on the opposite side of the body. The severity of the mice’s parkinsonism could then be assessed by measuring a characteristic rotating behavior, which is produced by a bias toward movement on one side that results from the asymmetrical deficit.

The researchers then set about exciting and inhibiting different populations of cells in the STN of the hemiparkinsonian mice, as may happen to these cells during DBS, and measuring the effect of these manipulations on the turning behavior, among other measures of the parkinsonian phenotype. After ruling out local excitatory neurons and glia, they found that high-frequency stimulation of axons in the STN that carry signals from other brain regions improved the mice’s phenotype. Like with DBS in humans, low-frequency stimulation was not effective, and by some measures even worsened the phenotype.


Further, high-frequency stimulation of a population of cells in the primary motor cortex (M1) from which some of the axons in the STN originated also improved the mice’s symptoms. Given that stimulation of the neurons influenced by these axons could not account for the improvement in phenotype, the researchers suggest that signals could be traveling backwards along the axon from the site of stimulation in the STN, relieving the parkinsonism by shifting activity in M1 away from low frequency bursting.


Though other mechanisms may still account for the efficacy of STN DBS, this research revealed a surprising mechanism by which DBS could improve Parkinson’s disease in humans, which was not intended at the time that STN DBS was originally developed. In addition, these results show the power of techniques for targeted dissection of neural circuits like optogenetics. Such methods have the potential to help researchers understand diseases and their treatments, and even provide insight in how to better target such treatments to improve their efficacy or reduce side effects.

To learn about Dr. Gradinaru’s current research, attend her talk on Tuesday, February 7th at 4 pm in the Marilyn G. Farquhar Seminar Room of the Center for Neural Circuits and Behavior.


Jacob Garrett is a first-year graduate student in the UCSD Neurosciences program, whose main interests within neuroscience include modeling and primary sensory systems.


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