Professional Education

  • Doctor of Philosophy, Stanford University, NEURS-PHD (2014)
  • Master of Science, Harvard University (2008)
  • Bachelor of Arts, Harvard University, Engineering (Biomedical) (2008)

Stanford Advisors

Lab Affiliations

All Publications

  • Shared Cortex-Cerebellum Dynamics in the Execution and Learning of a Motor Task CELL Wagner, M. J., Kim, T., Kadmon, J., Nguyen, N. D., Ganguli, S., Schnitzer, M. J., Luo, L. 2019; 177 (3): 669-+
  • Cerebellar granule cells encode the expectation of reward NATURE Wagner, M. J., Kim, T. H., Savall, J., Schnitzer, M. J., Luo, L. 2017; 544 (7648): 96-?


    The human brain contains approximately 60 billion cerebellar granule cells, which outnumber all other brain neurons combined. Classical theories posit that a large, diverse population of granule cells allows for highly detailed representations of sensorimotor context, enabling downstream Purkinje cells to sense fine contextual changes. Although evidence suggests a role for the cerebellum in cognition, granule cells are known to encode only sensory and motor context. Here, using two-photon calcium imaging in behaving mice, we show that granule cells convey information about the expectation of reward. Mice initiated voluntary forelimb movements for delayed sugar-water reward. Some granule cells responded preferentially to reward or reward omission, whereas others selectively encoded reward anticipation. Reward responses were not restricted to forelimb movement, as a Pavlovian task evoked similar responses. Compared to predictable rewards, unexpected rewards elicited markedly different granule cell activity despite identical stimuli and licking responses. In both tasks, reward signals were widespread throughout multiple cerebellar lobules. Tracking the same granule cells over several days of learning revealed that cells with reward-anticipating responses emerged from those that responded at the start of learning to reward delivery, whereas reward-omission responses grew stronger as learning progressed. The discovery of predictive, non-sensorimotor encoding in granule cells is a major departure from the current understanding of these neurons and markedly enriches the contextual information available to postsynaptic Purkinje cells, with important implications for cognitive processing in the cerebellum.

    View details for DOI 10.1038/nature21726

    View details for Web of Science ID 000398323300040

    View details for PubMedID 28321129

  • Skilled reaching tasks for head-fixed mice using a robotic manipulandum. Nature protocols Wagner, M. J., Savall, J., Kim, T. H., Schnitzer, M. J., Luo, L. 2020


    Skilled forelimb behaviors are among the most important for studying motor learning in multiple species including humans. This protocol describes learned forelimb tasks for mice using a two-axis robotic manipulandum. Our device provides a highly compact adaptation of actuated planar two-axis arms that is simple and inexpensive to construct. This paradigm has been dominant for decades in primate motor neuroscience. Our device can generate arbitrary virtual movement tracks, arbitrary time-varying forces or arbitrary position- or velocity-dependent force patterns. We describe several example tasks permitted by our device, including linear movements, movement sequences and aiming movements. We provide the mechanical drawings and source code needed to assemble and control the device, and detail the procedure to train mice to use the device. Our software can be simply extended to allow users to program various customized movement assays. The device can be assembled in a few days, and the time to train mice on the tasks that we describe ranges from a few days to several weeks. Furthermore, the device is compatible with various neurophysiological techniques that require head fixation.

    View details for DOI 10.1038/s41596-019-0286-8

    View details for PubMedID 32034393

  • Neocortex-Cerebellum Circuits for Cognitive Processing. Trends in neurosciences Wagner, M. J., Luo, L. 2019


    Although classically thought of as a motor circuit, the cerebellum is now understood to contribute to a wide variety of cognitive functions through its dense interconnections with the neocortex, the center of brain cognition. Recent investigations have shed light on the nature of cerebellar cognitive processing and information exchange with the neocortex. We review findings that demonstrate widespread reward-related cognitive input to the cerebellum, as well as new studies that have characterized the codependence of processing in the neocortex and cerebellum. Together, these data support a view of the neocortex-cerebellum circuit as a joint dynamic system both in classical sensorimotor contexts and reward-related, cognitive processing. These studies have also expanded classical theory on the computations performed by the cerebellar circuit.

    View details for DOI 10.1016/j.tins.2019.11.002

    View details for PubMedID 31787351

  • Shared Cortex-Cerebellum Dynamics in the Execution and Learning of a Motor Task. Cell Wagner, M. J., Kim, T. H., Kadmon, J., Nguyen, N. D., Ganguli, S., Schnitzer, M. J., Luo, L. 2019


    Throughout mammalian neocortex, layer 5 pyramidal (L5) cells project via the pons to a vast number of cerebellar granule cells (GrCs), forming a fundamental pathway. Yet, it is unknown how neuronal dynamics are transformed through the L5GrC pathway. Here, by directly comparing premotor L5 and GrC activity during a forelimb movement task using dual-site two-photon Ca2+ imaging, we found that in expert mice, L5 and GrC dynamics were highly similar. L5 cells and GrCs shared a common set of task-encoding activity patterns, possessed similar diversity of responses, and exhibited high correlations comparable to local correlations among L5 cells. Chronic imaging revealed that these dynamics co-emerged in cortex and cerebellum over learning: as behavioral performance improved, initially dissimilar L5 cells and GrCs converged onto a shared, low-dimensional, task-encoding set of neural activity patterns. Thus, a key function of cortico-cerebellar communication is the propagation of shared dynamics that emerge during learning.

    View details for PubMedID 30929904

  • Kilohertz two-photon brain imaging in awake mice. Nature methods Zhang, T., Hernandez, O., Chrapkiewicz, R., Shai, A., Wagner, M. J., Zhang, Y., Wu, C. H., Li, J. Z., Inoue, M., Gong, Y., Ahanonu, B., Zeng, H., Bito, H., Schnitzer, M. J. 2019


    Two-photon microscopy is a mainstay technique for imaging in scattering media and normally provides frame-acquisition rates of ~10-30 Hz. To track high-speed phenomena, we created a two-photon microscope with 400 illumination beams that collectively sample 95,000-211,000 µm2 areas at rates up to 1 kHz. Using this microscope, we visualized microcirculatory flow, fast venous constrictions and neuronal Ca2+ spiking with millisecond-scale timing resolution in the brains of awake mice.

    View details for DOI 10.1038/s41592-019-0597-2

    View details for PubMedID 31659327

  • Cognitive Signaling in Cerebellar Granule Cells. Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology Wagner, M. J. 2018; 43 (1): 222–23

    View details for PubMedID 29192666

    View details for PubMedCentralID PMC5719097

  • Cognitive Signaling in Cerebellar Granule Cells NEUROPSYCHOPHARMACOLOGY Wagner, M. J. 2018; 43 (1): 222–23
  • Imaging neural spiking in brain tissue using FRET-opsin protein voltage sensors NATURE COMMUNICATIONS Gong, Y., Wagner, M. J., Li, J. Z., Schnitzer, M. J. 2014; 5

    View details for DOI 10.1038/ncomms4674

    View details for Web of Science ID 000335221800005

    View details for PubMedID 24755708

  • Imaging neural spiking in brain tissue using FRET-opsin protein voltage sensors. Nature communications Gong, Y., Wagner, M. J., Zhong Li, J., Schnitzer, M. J. 2014; 5: 3674-?


    Genetically encoded fluorescence voltage sensors offer the possibility of directly visualizing neural spiking dynamics in cells targeted by their genetic class or connectivity. Sensors of this class have generally suffered performance-limiting tradeoffs between modest brightness, sluggish kinetics and limited signalling dynamic range in response to action potentials. Here we describe sensors that use fluorescence resonance energy transfer (FRET) to combine the rapid kinetics and substantial voltage-dependence of rhodopsin family voltage-sensing domains with the brightness of genetically engineered protein fluorophores. These FRET-opsin sensors significantly improve upon the spike detection fidelity offered by the genetically encoded voltage sensor, Arclight, while offering faster kinetics and higher brightness. Using FRET-opsin sensors we imaged neural spiking and sub-threshold membrane voltage dynamics in cultured neurons and in pyramidal cells within neocortical tissue slices. In live mice, rates and optical waveforms of cerebellar Purkinje neurons' dendritic voltage transients matched expectations for these cells' dendritic spikes.

    View details for DOI 10.1038/ncomms4674

    View details for PubMedID 24755708

  • Shared Internal Models for Feedforward and Feedback Control JOURNAL OF NEUROSCIENCE Wagner, M. J., Smith, M. A. 2008; 28 (42): 10663-10673


    A child often learns to ride a bicycle in the driveway, free of unforeseen obstacles. Yet when she first rides in the street, we hope that if a car suddenly pulls out in front of her, she will combine her innate goal of avoiding an accident with her learned knowledge of the bicycle, and steer away or brake. In general, when we train to perform a new motor task, our learning is most robust if it updates the rules of online error correction to reflect the rules and goals of the new task. Here we provide direct evidence that, after a new feedforward motor adaptation, motor feedback responses to unanticipated errors become precisely task appropriate, even when such errors were never experienced during training. To study this ability, we asked how, if at all, do online responses to occasional, unanticipated force pulses during reaching arm movements change after adapting to altered arm dynamics? Specifically, do they change in a task-appropriate manner? In our task, subjects learned novel velocity-dependent dynamics. However, occasional force-pulse perturbations produced unanticipated changes in velocity. Therefore, after adaptation, task-appropriate responses to unanticipated pulses should compensate corresponding changes in velocity-dependent dynamics. We found that after adaptation, pulse responses precisely compensated these changes, although they were never trained to do so. These results provide evidence for a smart feedback controller which automatically produces responses specific to the learned dynamics of the current task. To accomplish this, the neural processes underlying feedback control must (1) be capable of accurate real-time state prediction for velocity via a forward model and (2) have access to recently learned changes in internal models of limb dynamics.

    View details for DOI 10.1523/JNEUROSCI.5479-07.2008

    View details for Web of Science ID 000260060600021

    View details for PubMedID 18923042

  • Spaticitemporal linear decoding of brain state IEEE SIGNAL PROCESSING MAGAZINE Parra, L. C., Christoforou, C., Gerson, A. D., Dyrholm, M., Luo, A., Wagner, M., Philiastides, M. G., Sajda, P. 2008; 25 (1): 107-115