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Cortico-thalamic feedback loops for representational stabilization of visual sensation

Subject Area Experimental and Theoretical Network Neuroscience
Cognitive, Systems and Behavioural Neurobiology
Term since 2023
Project identifier Deutsche Forschungsgemeinschaft (DFG) - Project number 520285071
 
The response properties of neurons can change over time, even under seemingly constant input and output conditions. However, the factors governing such representational drift are mainly unknown. This project aims to understand how cortical feedback to the dorsal lateral geniculate nucleus (dLGN) interacts with local thalamic plasticity to determine the long-term stability of thalamic and cortical computations. In a tight experiment-theory collaboration, our project will record and model the stability of thalamic and cortical responses to varying visual stimuli in the presence or absence of corticothalamic feedback and local thalamic plasticity. Using two-photon microscopy, we will measure representational drift in the primary visual cortex (V1). Specifically, we will use chronic dual-color Ca2+-imaging to simultaneously record from thalamocortical projections and local V1 neuronal populations before and after timed perturbation of corticothalamic feedback or local thalamic plasticity. We will conduct longitudinal measurements of passive and active visual responses to quantify drift at the population and single cell level. Building on our expertise in designing models linking local neural circuit connectivity and ist corresponding activity, we will build a biologically realistic model capturing the selectivity and dynamics of cortical activity using the measured longitudinal responses, including their variability and temporal drift, across time. Our model will be based on the supralinear stabilized framework, which we previously used to infer local synaptic connectivity and input profiles. It can accurately represent the activity state and statistics of excitatory and inhibitory cortical firing rate responses neurons and their thalamic inputs. We aim to advance three specific goals. First, we will investigate the role of local dLGN plasticity in stabilizing representations of both thalamocortical neurons and simultaneously recorded V1 cortical networks. Second, we will test our central hypothesis that corticothalamic feedback exerts a stabilizing influence on thalamic and cortical visual representations. Third, we will develop a dynamical, biologically inspired network model of thalamo-cortico-thalamic representational stabilization to test if we can provide a minimally consistent model that accounts for our experimental findings and provides further testable predictions. In summary, this project will connect the feedforward and feedback connectivity to the emergence and control of cortical representational drift.
DFG Programme Priority Programmes
 
 

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