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.
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.
People |
ORCID iD |
Federico Turkheimer (Primary Supervisor) | |
Eilidh MacNicol (Student) |
Publications
Brusini I
(2022)
MRI-derived brain age as a biomarker of ageing in rats: validation using a healthy lifestyle intervention.
in Neurobiology of aging
MacNicol E
(2020)
Atlas-based brain extraction is robust across rat MRI studies
MacNicol E
(2021)
Age-specific adult rat brain MRI templates and tissue probability maps
MacNicol E
(2021)
Atlas-Based Brain Extraction Is Robust Across RAT MRI Studies
MacNicol E
(2021)
Age-Specific Adult Rat Brain MRI Templates and Tissue Probability Maps.
in Frontiers in neuroinformatics
Studentship Projects
Project Reference | Relationship | Related To | Start | End | Student Name |
---|---|---|---|---|---|
MR/N013700/1 | 30/09/2016 | 29/09/2025 | |||
1855722 | Studentship | MR/N013700/1 | 30/09/2016 | 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 |