The patterns of muscle activation that drive mammalian movement reflect an interplay between networks of neurons in the spinal cord and neurons in an array of brain regions that comprise the motor system. Our research combines novel genetically-mediated approaches for measuring and perturbing activity in neuronal subpopulations with quantitative and model-based analyses to understand how descending projections steer movement. Here are some examples of our current interests:
Skilled movement generation in real time – Motor skills are movements that animals improve with repeated practice. The capacity to improve motor behaviors is vital to the fitness these behaviors confer, and so to the evolutionary success of many mammalian species. Many motor system regions appear critical for driving motor skills, but it is unclear how these regions interact in real time to ensure such movements are properly orchestrated. Our approach is behavior-centric, exploring how neuronal populations within motor system regions conspire to execute a model skilled movement. We draw on our experience developing training paradigms in which mice learn skilled forelimb movements, which have opened up a wealth of experimental possibilities. We assess interactions between neuronal populations by combining rapid activity perturbations via optogenetic probes with large-scale electrical and optical activity measurement in one or more populations as movements are executed. Simultaneous forelimb electromyography (EMG) provides a high temporal resolution readout of motor system output.
Understanding the cortical orchestration of movement – Motor areas of the brain’s neocortex play a particular role in facilitating the remarkable complexity and agility of mammalian movement, but we understand little about how. In contrast to previous approaches that have assessed cortical function with respect to movement type, we focus on how motor cortical influence depends on the underlying muscle activation patterns themselves, which we quantify via EMG. Our approach relies on the temporal resolution of optogenetic inactivation methods, the development of freely-behaving paradigms in which mice express a broad range of natural movements, and the use of contemporary dimensionality reduction methods to classify muscle activation patterns. Our recent findings suggest that there are certain components of motor cortical output activity that directly drive muscles, while other components may serve other roles. Coupling activity measurement and perturbation here will allow us to further investigate this sort of functional discretization among motor cortical output components.
Identifying the functional units of corticospinal control – The resolution of subatomic particles or of DNA structure illustrate how mechanistic insight can rapidly mount after the appropriate functional units for explaining a given phenomenon are identified. However for many neural processes, the appropriate functional units for describing the underlying mechanism remain unclear. The continued development of viral tracing strategies and cellular-resolution genomic methods for delineating neuronal subtypes now enable us to address this ambiguity in a new way. We aim to characterize the relationship between neuronal identity and function within the corticospinal population by combining two-photon imaging of neural activity in mice performing skilled forelimb movements together with genetic access to subtypes defined by transcriptomic state, projection patterns, and postsynaptic partner identity. Dimensionality reduction-based analyses will enable unbiased assessment of coactive functional groups among corticospinal neurons that can be registered with subtype identity. By resolving how corticospinal neuron features align with function, light will be shed on the appropriate functional elements with which to describe motor system operation.
Here's a video of a recent talk Andrew gave.
Abhishek Sarup, M.S.
Pouyan Kheirkhah, M.D.
Behaviorally-selective engagement of short-latency effector pathways by motor cortex.
Miri, A., Warriner, C.L., Seely, J.S., Elsayed, G.F., Cunningham, J.P., Churchland, M.M., Jessell, T.M. (2017). Neuron 95(3):683-696.
Primacy of flexor locomotor pattern revealed by ancestral reversion of motor neuron identity.
Machado, T.A., Pnevmatikakis, E., Paninski, L., Jessell, T.M., Miri, A. (2015). Cell 162(2):338-50.
Spatial gradients and
multidimensional dynamics in a neural integrator circuit.
Miri, A., Daie, K., Arrenberg, A.B., Baier, H., Aksay, E., Tank, D.W. (2011). Nature Neuroscience 14(9):1150-11.
Regression-based identification of behavior-encoding neurons during large scale optical imaging of neural activity at cellular resolution.
Miri, A., Daie, K., Burdine, R.D., Aksay, E., Tank, D.W. (2011). Journal of Neurophysiology 105(2):964-980.
We are actively recruiting postdocs to join the lab. Previous experience with electrophysiology and/or 2-photon imaging is preferred but definitely not required. If you are interested, please email Andrew (email@example.com).
We are also actively recruiting graduate students. Please contact Andrew directly.
Andrew Miri, Ph.D.
Department of Neurobiology
2205 Tech Drive
2-115 Pancoe Hall
Evanston, IL 60201