BBSRC EASTBIO DTP - How learning modifies neuronal population codes in the visual cortex during the acquisition of a behavioural task

Our ability to learn relies on the potential of neuronal circuits to change through experience. The overall theme of this project is to understand how cortical circuits are modified by experience. In this project, a computer science and a neurophysiology research group join strengths to apply the latest methodologies from image processing and machine learning, to analyse and interpret imaging data of cortical network activity. The PhD student will receive training in working at the life sciences/computing interface since the project combines state-of-the art neurophysiology with computational methods of data analysis.

Since the discoveries of Hubel and Wiesel 50 years ago, plasticity in the primary visual cortex has become a popular system for studying how neuronal circuits in the neocortex are modified by experience. It is known that the primary visual cortex is a site of experience-dependent plasticity either after deprivation or after repeated visual experience. Several studies indicate that inhibition plays an important role in this process both during development and in adults where a decrease in inhibition is thought to reactivate functional plasticity and promote functional recovery, for example after retinal or visual cortex lesions. However, the cellular and synaptic mechanisms underlying the role of inhibition in experience-dependent plasticity remain largely unexplored.

The aim of this project is to characterize the activity of different types of inhibitory and excitatory neurons in the adult mouse primary visual cortex (V1), during the learning of a visually-guided behaviour. To this aim, the student will be trained and will apply the technique of two-photon calcium imaging that allows in vivo imaging of the activity of large neuronal populations with single-cell resolution, in awake behaving mice (Peron et al., 2015). The activity of the different neuronal populations will be monitored before, during and after the acquisition of a behavioural task acquired in a virtual reality environment. The mice will be trained to recognize, along the virtual track, a visual cue associated with a reward. The project is organized around 3 aims:

Aim 1. To image the activity of large populations of neurons in layers 2/3 and 4, before, during and after the learning of the behavioural task. By using 3-D two-photon imaging, somatic calcium responses of neurons expressing a genetically-encoded calcium indicator in layer 2/3 and layer 4 will be imaged.

Aim 2. Development of analysis tools for big imaging data. This aim will benefit from the results obtained in the framework of a BBSRC grant awarded to the two supervisors of this project (call: Support for development of bioinformatics tools and computational approaches to the biosciences; title: FOCIA: Fast, Open, Cellular Imaging Analysis toolbox). These methods will be used for the analysis of the functional organization of population activity and its changes during the learning of the behavioural task.

Aim 3. The findings in aims 1 and 2 will be synthesized in a computational model of experience-dependent plasticity in granular and supragranular layers in the primary visual cortex.

This interdisciplinary project is combining state-of-the art in vivo imaging with powerful analysis and computational methods applied to big neuronal population activity. Both the imaging method and the behavioural task are already established in the laboratory. Imaging data obtained in the 2-photon set-up of the lab have recently been published (Pakan et al., 2016).