Active visual processing; Visual cortex; Two-photon imaging; Electrophysiology; Optogenetics; Mouse vision; Neuroscience; Sensorimotor integration
Zmarz Pawel, Keller Georg B, Mismatch Receptive Fields in Mouse Visual Cortex., in Neuron
, 92(4), 766-772.
Wertz Adrian, Trenholm Stuart, Yonehara Keisuke, Hillier Daniel, Raics Zoltan, Leinweber Marcus, Szalay Gergely, Ghanem Alexander, Keller Georg, Rózsa Balázs, Conzelmann Karl-Klaus, Roska Botond, PRESYNAPTIC NETWORKS. Single-cell-initiated monosynaptic tracing reveals layer-specific cortical network modules., in Science (New York, N.Y.)
, 349(6243), 70-4.
Keller Andreas J, Houlton Rachael, Kampa Björn M, Lesica Nicholas A, Mrsic-Flogel Thomas D, Keller Georg B, Helmchen Fritjof, Stimulus relevance modulates contrast adaptation in visual cortex., in eLife
, 6(n/a), n/a-n/a.
Barnes Samuel J, Sammons Rosanna P, Jacobsen R Irene, Mackie Jennifer, Keller Georg B, Keck Tara, Subnetwork-Specific Homeostatic Plasticity in Mouse Visual Cortex In Vivo., in Neuron
, 86(5), 1290-303.
I here propose to investigate sensorimotor learning using the mouse visual cortex as a model system. In classical terms, visual perception is described as a feed-forward processing hierarchy in the form of a sequence of more and more complex filters. Recent evidence, however, has brought the completeness of this description to question. There is accumulating evidence for non-sensory, motor-related signals in primary sensory areas of cortex. A large fraction of the activity in primary visual cortex (V1), for example, persists even in the complete absence of visual input and seems to be driven purely by motor output. In addition we, and others, could show that there are strong feedback mismatch signals in both primary visual and auditory areas of cortex, potentially encoding a difference between actual and predicted sensory feedback. This suggests that primary sensory areas of cortex are actively involved in sensorimotor learning, in that they may provide the mismatch, or “error”, signal necessary for motor adaptation. However, it is still unclear what the source of the motor related signals in V1 is that underlie this computation. We have recently been able to identify the anterior cingulate cortex (ACC), a supplementary motor area, as one source of motor related activity in primary visual cortex of the mouse. I now propose to investigate sensorimotor learning both on the basis of this connection between ACC and V1, as well as in terms of the functional and the genetic changes involved. To this end we will characterize motor related inputs to V1 functionally and anatomically using a combination of two-photon imaging and optogenetic stimulation in the behaving mouse, as well as methods of viral circuit mapping. In addition we will use virtual reality environments, which allow us to alter sensorimotor contingencies, to measure the functional changes underlying sensorimotor learning. This research is of importance not only because visual cortex serves as a model for our understanding of cortical function in general, but because sensorimotor dysfunction is characteristic of many developmental and psychological disorders. Dysfunction of ACC and possibly its communication with sensory areas of cortex, for example, are implicated in schizophrenia. Interpretation of such findings is complicated by the fact that only comparably little is known about the function of ACC or the neural substrate of sensorimotor learning in general. Using the techniques we developed we can now address questions of sensorimotor learning and specifically the involvement of ACC in this process in a mouse model. I am confident that our work will contribute to a more thorough understanding of both the function of visual cortex and of the mechanisms of sensorimotor learning, and specifically may lay the foundation for a new approach to investigating the neural basis of sensorimotor dysfunction.