About the Project
Memories are thought to be stored as traces distributed across the brain. How these memory traces
are coordinated is a fundamental unsolved problem. This project aims to address this problem by investigating outputs from a brain structure called the entorhinal cortex. This structure is of great interest as it receives signals from the hippocampus, which is important for initial learning, and sends outputs to diverse cortical targets that together are important for long-term memory (Frankland and Bontempi 2005). The proposed project involves carrying out experiments in rodents using advanced genetic and physiological methods to establish organising principles by which the entorhinal cortex coordinates neural activity within and between cortical regions. It will use microscopic cameras (Jercog, Rogerson, and Schnitzer 2016) to monitor cortical activity of thousands of genetically accessed neurons simultaneously during visuospatial learning and test influences of projections from the entorhinal cortex. These studies will help to identify the neural substrates for long-term memories and to explain how disparate cortical areas generate coherent cognitive states.
What transformations do cortical networks undergo as memories are formed? What roles does
MEC play in these cortical network changes? Following consolidation of memories there
appears to be a shift in activity from deep to superficial layers. This suggests a model in which
neurons in deep layers receive MEC input and coordinate plasticity of connections between
more superficial associational neurons; according to this model as learning progresses
associational connections between superficial neurons in different cortical areas may play a
greater role in generating memory-related activity. To test this model we will image activity
of neurons defined according to their connectivity with MEC and their projections to other
cortical areas using genetically engineered calcium indicators (GCaMP6). We will then test the necessity of the MEC L5a neurons for task feature-related cortical activity
These experiments will generate very large and rich datasets, which will help unravel the fundamental principles of the neural basis of memory. Since memory engrams are typically sparse and highly distributed over many neurons, tracking the acquisition of new memories will require advanced analysis methods, which will be developed in collaboration with the second supervisor based in the School of Informatics.
Moreover, the results will enable constructing new models of short and long-term memory acquisition that can advance artificial neural networks used in machine learning applications. Therefore, this project will provide not only extensive training in functional neuron imaging in vivo, but also the application of computational methods for data analysis, interpretation and modelling, a valuable skill set for research in systems neuroscience.
10. Jercog, P., Rogerson, T. & Schnitzer, M. J. Large-Scale Fluorescence Calcium-Imaging Methods for Studies of Long-Term Memory in Behaving Mammals. Cold Spring Harb. Perspect. Biol. 8, (2016).
Frankland, P. W. & Bontempi, B. The organization of recent and remote memories. Nat. Rev. Neurosci. 6, 119–130 (2005).
Sürmeli, G. et al. Molecularly Defined Circuitry Reveals Input-Output Segregation in Deep Layers of the Medial Entorhinal Cortex. Neuron 88, 1040–1053 (2015).
Completed application form along with your supporting documents should be sent to our PGR student team at firstname.lastname@example.org by 5th January 2020.
References: Please send the reference request form to two referees. Completed references for this project should also be returned to email@example.com by the closing date: 5th January 2020.
It is your responsibility to ensure that references are provided by the specified deadline.
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