3 research outputs found
Local circuit amplification of spatial selectivity in the hippocampus
Local circuit architecture facilitates the emergence of feature selectivity in the cerebral cortex1. In the hippocampus, it remains unknown whether local computations supported by specific connectivity motifs2 regulate the spatial receptive fields of pyramidal cells3. Here we developed an in vivo electroporation method for monosynaptic retrograde tracing4 and optogenetics manipulation at single-cell resolution to interrogate the dynamic interaction of place cells with their microcircuitry during navigation. We found a local circuit mechanism in CA1 whereby the spatial tuning of an individual place cell can propagate to a functionally recurrent subnetwork5 to which it belongs. The emergence of place fields in individual neurons led to the development of inverse selectivity in a subset of their presynaptic interneurons, and recruited functionally coupled place cells at that location. Thus, the spatial selectivity of single CA1 neurons is amplified through local circuit plasticity to enable effective multi-neuronal representations that can flexibly scale environmental features locally without degrading the feedforward input structure
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Neural circuit control of feature tuning in CA1 during spatial learning
The world is a complex and dynamic place. The incredibly dense and constantly changing information stream with which our senses are bombarded must be decomposed, taken in, and processed by any organism hoping to make enough sense of this world in order to survive to the next moment. For complex behaviors, and in particular a great many of those that we often feel define us as a human species, this dense sensory stream must not just be processed, but the important features of the environment must be further distilled and structured into representations that can then be stored long-term to guide future behavior through the joint processes of Learning and Memory. The primary goal of this thesis is to further our understanding of the neurobiological bases - at the subcellular, circuit, and network level - of learning and memory.
The hippocampus, one of the most studied systems in the brain by far, is thought to play a central role in learning and memory. Principal cells in the hippocampus become tuned to environmental features, forming persistent representations of an animal’s environment, but the precise mechanisms by which these representations are formed, used, and maintained remain unresolved. By employing a variety of experimental techniques including in vivo two-photon calcium imaging, extracellular electrophysiology, optogenetics, and chemogenetics in awake, behaving mice, we attempted to characterize the subcellular and circuit determinants of place field representations and to connect them to these cells’ role in spatial learning and memory
Local circuit amplification of spatial selectivity in the hippocampus
Local circuit architecture facilitates the emergence of feature selectivity in the cerebral cortex1. In the hippocampus, it remains unknown whether local computations supported by specific connectivity motifs2 regulate the spatial receptive fields of pyramidal cells3. Here we developed an in vivo electroporation method for monosynaptic retrograde tracing4 and optogenetics manipulation at single-cell resolution to interrogate the dynamic interaction of place cells with their microcircuitry during navigation. We found a local circuit mechanism in CA1 whereby the spatial tuning of an individual place cell can propagate to a functionally recurrent subnetwork5 to which it belongs. The emergence of place fields in individual neurons led to the development of inverse selectivity in a subset of their presynaptic interneurons, and recruited functionally coupled place cells at that location. Thus, the spatial selectivity of single CA1 neurons is amplified through local circuit plasticity to enable effective multi-neuronal representations that can flexibly scale environmental features locally without degrading the feedforward input structure