8The process by which visual information is incorporated into the brain's spatial framework 9to represent landmarks is poorly understood. Studies in humans and rodents suggest that 10 retrosplenial cortex (RSC) plays a key role in these computations. We developed an RSC-11 dependent behavioral task in which head-fixed mice learned the spatial relationship 12 between visual landmark cues and hidden reward locations. Two-photon imaging 13revealed that these cues served as dominant reference points for most task-active 14neurons and anchored the spatial code in RSC. Presenting the same environment but 15 decoupled from mouse behavior degraded encoding fidelity. Analyzing visual and motor 16responses showed that landmark codes were the result of supralinear integration. 17Surprisingly, V1 axons recorded in RSC showed similar receptive fields. However, they 18 were less modulated by task engagement, indicating that landmark representations in 19RSC are the result of local computations. Our data provide cellular-and network-level 20insight into how RSC represents landmarks. 21 22
The process by which visual information is incorporated into the brain’s spatial framework to represent landmarks is poorly understood. Studies in humans and rodents suggest that retrosplenial cortex (RSC) plays a key role in these computations. We developed an RSC-dependent behavioral task in which head-fixed mice learned the spatial relationship between visual landmark cues and hidden reward locations. Two-photon imaging revealed that these cues served as dominant reference points for most task-active neurons and anchored the spatial code in RSC. This encoding was more robust after task acquisition. Decoupling the virtual environment from mouse behavior degraded spatial representations and provided evidence that supralinear integration of visual and motor inputs contributes to landmark encoding. V1 axons recorded in RSC were less modulated by task engagement but showed surprisingly similar spatial tuning. Our data indicate that landmark representations in RSC are the result of local integration of visual, motor, and spatial information.
Dendrites receive the vast majority of a single neuron's inputs, and coordinate the transformation of these signals into neuronal output.Ex vivoand theoretical evidence has shown that dendrites possess powerful processing capabilities, yet little is known about how these mechanisms are engaged in the intact brain or how they influence circuit dynamics. New experimental and computational technologies have led to a surge in interest to unravel and harness their computational potential. This review highlights recent and emerging work that combines established and cutting-edge technologies to identify the role of dendrites in brain function. We discuss active dendritic mediation of sensory perception and learning in neocortical and hippocampal pyramidal neurons. Complementing these physiological findings, we present theoretical work that provides new insights into the underlying computations of single neurons and networks by using biologically plausible implementations of dendritic processes. Finally, we present a novel brain–computer interface task, which assays somatodendritic coupling to study the mechanisms of biological credit assignment. Together, these findings present exciting progress in understanding how dendrites are critical forin vivolearning and behavior, and highlight how subcellular processes can contribute to our understanding of both biological and artificial neural computation.
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