Neurotransmitter Systems and their role in Cognitive and Metabolic Reserve in Ageing

Lead Research Organisation: King's College London
Department Name: Neuroscience

Abstract

During healthy ageing, network structure and function deteriorates but individual differences appear to moderate cognitive decline to some extent. Previous work has concluded that variations in cholinergic basal forebrain (ChBF) atrophy influences the degree of cognitive reserve, (i.e. the magnitude of a buffer from a critical point, beyond which competence diminishes). Similarly, environmental factors contribute to the level of metabolic reserve, which is the extent of cell functioning compared to its maximum metabolic capacity. This leads to further individual differences in resisting cell dysfunction, which can ultimately engender retention of cognitive faculties.

This work aims to investigate the mechanisms allowing cholinergic projections to promote alternative white matter connections, in order to preserve cognitive network function. It will also explore individual differences in metabolic and cognitive reserve in ageing, and how they relate to cholinergic and other transmitter systems, with the intention of gaining insight into their mechanisms and illuminating potential therapy targets. This work will include analysis of human MRI scans and cognitive testing to determine how ChBF atrophy, functional connectivity, and cognition are related. As new techniques emerge, this work can be extended to other transmitter systems; for instance, neuromelanin-weighted MRI utilises magnetisation transfer principles to quantify atrophy of dopaminergic and noradrenergic nuclei in humans. Furthermore, this project will examine underlying reserve mechanisms by using rat models to study the relationship between the cholinergic system and metabolic reserve, employing MRI before and after injections of metabolism-boosting methylene blue, and histological techniques.

Publications

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Studentship Projects

Project Reference Relationship Related To Start End Student Name
MR/N013700/1 01/10/2016 30/09/2025
1855722 Studentship MR/N013700/1 01/10/2016 31/12/2020 Eilidh MacNicol
 
Description MRC Flexible Supplement Fund
Amount £4,989 (GBP)
Organisation Medical Research Council (MRC) 
Sector Public
Country United Kingdom
Start 01/2020 
End 09/2020
 
Description fMRIPrep for Rodents 
Organisation Stanford University
Department Stanford Center for Reproducible Neuroscience
Country United States 
Sector Academic/University 
PI Contribution Contributing expertise of rodent MRI, rodent data for testing, and intellectual input on creating software
Collaborator Contribution Provided training for creating and releasing software, the expertise of reproducible neuroimaging preprocessing pipelines, intellectual input on creating software, and working space at Stanford University.
Impact Federation of European Neuroscience Societies (FENS) poster (withdrawn): NiRodents: standardized MRI preprocessing tools for the preclinical imaging community. (2020) MacNicol, Ciric, Kim, Cash, Poldrack, & Esteban. Multidisciplinary collaboration (neuroscience, computer science, medical physics) MacNicol, Eilidh, Rastko Ciric, Eugene Kim, Davide DiCenso, Diana Cash, Russell Poldrack, and Oscar Esteban. 2020. "Atlas-based Brain Extraction Is Robust Across Rat MRI Studies." OSF Preprints. October 25. doi:10.31219/osf.io/sqxef. Esteban, Oscar, Azeez Adebimpe, Christopher J. Markiewicz, Mathias Goncalves, Ross W. Blair, Matthew Cieslak, Mikaël Naveau, et al. 2021. "The Bermuda Triangle of D- and F-mri Sailors - Software for Susceptibility Distortions (sdcflows)." OSF Preprints. February 1. doi:10.31219/osf.io/gy8nt
Start Year 2020
 
Title NiRodents 
Description NiRodents intends to reliably adapt human-specific workflows for non-human data to improve translation between human and preclinical MRI by building congruence between the fields. It is an open-source Python package available on GitHub (nipreps/nirodents), released under an Apache License 2.0, and distributed via Pypi or Linux containers. 
Type Of Technology Software 
Year Produced 2020 
Open Source License? Yes  
Impact The first tool from NiRodents is artsBrainExtraction, which modifies the popular atlas-based brain extraction tool, antsBrainExtraction, for rodent MRI. It reliably extracts brains while being robust to heterogeneous data inputs, as it is agnostic to the imaging protocol, and can be extended to further image modalities and non-human populations. 
URL https://github.com/nipreps/nirodents
 
Title fMRIPrep-Rodents 
Description fMRIPrep has induced a paradigm shift in neuroimaging by popularising a standard preprocessing workflow for human fMRI data that is reliable across studies, allowing researchers to focus on data analysis. fMRIPrep-Rodents adapt fMRIPrep's workflow to rodent imaging, providing preclinical researchers with the same paradigm shift. With fMRIPrep-rodents, researchers can use a well-established and robust preprocessing workflow that is optimised for rodents. 
Type Of Technology Software 
Year Produced 2021 
Open Source License? Yes  
Impact fMRIPrep-rodents plans to extend standardised processing and provides confidence in data quality, which benefits the rodent imaging community, but also the larger neuroimaging community. By providing a tool that delivers a standardised pipeline for rodent fMRI preprocessing but is consistent with the tools used in humans, it will facilitate generalizability between rodent experiments, and greater consistency is expected for translational experiments. 
URL https://github.com/poldracklab/fmriprep-rodents