Internal representation of familiar environments in visual cortex

Year of award: 2023


  • Dr Alfredo Llorca Molina

    University of Edinburgh, United Kingdom

Project summary

Throughout our life, our brain forms internal models of the world based on our experiences. Such internal models are used to predict sensory information and adapt our behaviour to the demands of the environment. I hypothesize that primary visual cortex (V1) encodes internal representations of previously experienced visual environments and that these representations are activated when they are behaviourally relevant. To test this hypothesis, I will record the activity of large neuronal populations in V1 of awake mice navigating a familiar virtual environment in darkness. I will combine in vivo recordings with optogenetics to identify the top-down cortical circuits evoking these responses, as well as the local circuits within V1 gating these internal representations and integrating them with external sensory inputs. This proposal has three key goals: 1: Determine the encoding of spatial cues in mouse V1 while animals navigate a familiar environment in darkness 2: Determine the cortical circuits conveying spatial information to V1 in the absence of visual cues 3: Determine the local circuits gating spatial information in V1 in the presence and absence of visual information. Keywords: Visual cortex; Cortical circuits; Spatial expectations; Awake mice; Navigation. Virtual reality. Two-photon calcium imaging. Inhibitory neurons. Feedback projections.