MRI Studies of Appetite Centre Function in Rodents

Many different regions of the brain are involved in appetite control. A full understanding of their function and interaction requires studying neuronal activity at high resolution simultaneously in space and time. Two Magnetic Resonance Imaging (MRI) methods can potentially achieve this goal. Manganese-Enhanced (MEMRI) uses the accumulation of administered Mn[2+], which is paramagnetic (hence MRI visible) and taken up by active neurons through voltage-gated Ca[2+] channels during action potentials. Haemodynamic methods use one or more of many MRI-visible changes that occur to circulating blood in a brain region when it changes activity. These include blood-oxygenation level dependent (BOLD) and cerebral blood volume weighted (CBV) MRI. The aim of this project was to further develop, adapt and then use these methods to study the effects on neuronal activity of stimuli related to appetite and energy balance. The majority of work went towards adapting MEMRI for this. Amongst many tested changes, improvements were made to the MRI acquisition protocol (specifically using fast spin echo rather than spin-echo acquisition) to make it more sensitive to Mn-induced signal changes, increase spatial coverage from partial to whole brain and rostro-caudal spatial resolution from 1 to 0.4mm, all while maintaining the same temporal resolution. Most importantly, the neuroimaging analysis framework used in haemodynamic functional MRI was adapted for use with MEMRI. This included the adaptation of spatial normalization software to handle Mn-sensitive T[1]-weighted images dominated by non-brain tissue rather than brain dominated T[2]/T*[2]-weighted images, and the generation of a signal change model for use in GLM. This enabled much more objective, reproducible and less laborious data analysis than with previous hand drawn ROIs. Attempts were made to use BOLD- and CBV-fMRI to study the effects of potent, appetite-modulating gut hormones on appetite, though these failed to produce a response

MRI studies of appetite centre function in rodents

Many different regions of the brain are involved in appetite control. A full understanding of their function and interaction requires studying neuronal activity at high resolution simultaneously in space and time. Two Magnetic Resonance Imaging (MRI) methods can potentially achieve this goal. Manganese-Enhanced (MEMRI) uses the accumulation of administered Mn[2+], which is paramagnetic (hence MRI visible) and taken up by active neurons through voltage-gated Ca[2+] channels during action potentials. Haemodynamic methods use one or more of many MRI-visible changes that occur to circulating blood in a brain region when it changes activity. These include blood-oxygenation level dependent (BOLD) and cerebral blood volume weighted (CBV) MRI. The aim of this project was to further develop, adapt and then use these methods to study the effects on neuronal activity of stimuli related to appetite and energy balance. The majority of work went towards adapting MEMRI for this. Amongst many tested changes, improvements were made to the MRI acquisition protocol (specifically using fast spin echo rather than spin-echo acquisition) to make it more sensitive to Mn-induced signal changes, increase spatial coverage from partial to whole brain and rostro-caudal spatial resolution from 1 to 0.4mm, all while maintaining the same temporal resolution. Most importantly, the neuroimaging analysis framework used in haemodynamic functional MRI was adapted for use with MEMRI. This included the adaptation of spatial normalization software to handle Mn-sensitive T[1]-weighted images dominated by non-brain tissue rather than brain dominated T[2]/T*[2]-weighted images, and the generation of a signal change model for use in GLM. This enabled much more objective, reproducible and less laborious data analysis than with previous hand drawn ROIs. Attempts were made to use BOLD- and CBV-fMRI to study the effects of potent, appetite-modulating gut hormones on appetite, though these failed to produce a response.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Common functional networks in the mouse brain revealed by multi-centre resting-state fMRI analysis

Preclinical applications of resting-state functional magnetic resonance imaging (rsfMRI) offer the possibility to non-invasively probe whole-brain network dynamics and to investigate the determinants of altered network signatures observed in human studies. Mouse rsfMRI has been increasingly adopted by numerous laboratories worldwide. Here we describe a multi-centre comparison of 17 mouse rsfMRI datasets via a common image processing and analysis pipeline. Despite prominent cross-laboratory differences in equipment and imaging procedures, we report the reproducible identification of several large-scale resting-state networks (RSN), including a mouse default-mode network, in the majority of datasets. A combination of factors was associated with enhanced reproducibility in functional connectivity parameter estimation, including animal handling procedures and equipment performance. RSN spatial specificity was enhanced in datasets acquired at higher field strength, with cryoprobes, in ventilated animals, and under medetomidine-isoflurane combination sedation. Our work describes a set of representative RSNs in the mouse brain and highlights key experimental parameters that can critically guide the design and analysis of future rodent rsfMRI investigations

Common functional networks in the mouse brain revealed by multi-centre resting-state fMRI analysis.

Preclinical applications of resting-state functional magnetic resonance imaging (rsfMRI) offer the possibility to non-invasively probe whole-brain network dynamics and to investigate the determinants of altered network signatures observed in human studies. Mouse rsfMRI has been increasingly adopted by numerous laboratories worldwide. Here we describe a multi-centre comparison of 17 mouse rsfMRI datasets via a common image processing and analysis pipeline. Despite prominent cross-laboratory differences in equipment and imaging procedures, we report the reproducible identification of several large-scale resting-state networks (RSN), including a mouse default-mode network, in the majority of datasets. A combination of factors was associated with enhanced reproducibility in functional connectivity parameter estimation, including animal handling procedures and equipment performance. RSN spatial specificity was enhanced in datasets acquired at higher field strength, with cryoprobes, in ventilated animals, and under medetomidine-isoflurane combination sedation. Our work describes a set of representative RSNs in the mouse brain and highlights key experimental parameters that can critically guide the design and analysis of future rodent rsfMRI investigations