243 Mellon Institute
Department of Biological Sciences
Carnegie Mellon University
4400 Fifth Avenue
Pittsburgh, PA 15213
Ph.D., Neuroscience, Washington University in St. Louis
B.S., Neuroscience, College of William and Mary
The selection of actions is central to how we interact with the world, a reality that is often not fully appreciated until this ability is lost through impairments like stroke and Parkinson's disease. Our goal is to establish how neural circuits lead to these action selection decisions. The vital ability to make appropriate actions requires the coordination of motor, reward, and cognitive brain systems. While compelling research has been accomplished in individual brain areas, studying elements of neuronal circuits in isolation yields an incomplete and potentially misleading picture. Our research approach is inclusive yet specific: interrogating the functional interactions between areas in a manner more typical of cognitive neuroscience (e.g. fMRI) while also identifying the computational contributions of individual cell types within each region.
To establish the neural computations underlying behavior, we monitor the electrical activity of hundreds of individual neurons simultaneously. This feat is made possible using technology we helped design that records from an order of magnitude more neurons than the current state of the art permits. We have also developed unique computational methods to distill and analyze these data in new and meaningful ways.
Congruently, we believe that the function of circuits can only be understood relative to the careful application of behavioral paradigms. To this end, we apply nonhuman primate-like methods for studying attention, motor planning and behavioral economics to propel the lab forward, asking detailed behavioral questions previously thought to be inaccessible in a mouse model. With this approach, we can train complex behaviors, like reaching for a target, while also extracting detailed quantitative measures, permitting more accurate and comprehensive study of the neural mechanisms at play.
Our research in the Yttri Lab uses these electrophysiological, behavioral, and computational tools to build upon the distributed action execution model established previously (Yttri and Dudman, Nature 2016), delineating a specific role for each individual cell type in the motor system. Future work will leverage these findings into new therapeutic strategies for conditions such as Parkinson’s disease, improving deep brain stimulators in collaboration with neurosurgeons.
Hsu AI, Yttri EA. B-SOiD: An Open Source Unsupervised Algorithm for Identification and Fast Prediction of Behaviors. Nature Communications, 2021.
Geramita MA, Yttri EA, Ahmari SE. The two‐step task, avoidance, and OCD. Journal of Neuroscience Research, 2020.
Belsey PP, Nicholas MA, Yttri EA. Open-Source Joystick Manipulandum for DecisionMaking, Reaching, and Motor Control Studies in Mice. eNeuro, 2020
Gittis AH, Yttri EA. Translating insights from optogenetics into therapies for Parkinson’s disease. Current Opinion in Biomedical Engineering, 2018.
Yttri EA, Dudman JT. A proposed circuit computation in basal ganglia: History-dependent gain. Mov Disord. 2018 Mar 24. doi: 10.1002/mds.27321. [Epub ahead of print] PMID: 29575303
Yttri EA, Dudman JT. Opponent and bidirectional selection of movement parameters in the basal ganglia. Nature, 2016.
Yttri EA, Dudman JT. Invited manuscript in Movement Disorders, “Scientific Perspectives” a review and clinical elaboration of our recent work.
Yttri EA, Martin KA, Dudman JT. Complete representation of movement execution in striatal ensembles.
Yttri EA, Wang C, Liu Y, Snyder LH. The parietal reach region is limb specific and not involved in eye-hand coordination. Journal of Neurophysiology, 2014.
Yttri EA, Liu Y, Snyder LH. Lesions of cortical area LIP affect reach onset only when the reach is accompanied by a saccade, revealing an active eye-hand coordination circuit. Proceedings of the National Academy of Science, USA, 2013.
Liu Y, Yttri EA, Snyder LH. Intention and attention: different functional roles for LIPd and LIPv. Nature Neuroscience, 2010.
Reid EK, Norris SA, Taylor JA, Hathaway EN, Smith AJ, Yttri EA, Thach WT. Is the parvocellular red nucleus involved in cerebellar motor learning? Current Trends in Neurology, 2010.