Abstract
When the sensory cortex is stimulated and directly receiving afferent input, modulations can also be observed in the activity of other brain regions comprising spatially distributed, yet intrinsically connected networks, suggesting that these networks support brain function during task performance. Such networks can exhibit subtle or unpredictable task responses which can pass undetected by conventional general linear modelling (GLM). Additionally, the metabolic demand of these networks in response to stimulation remains incompletely understood. Here, we recorded concurrent BOLD and CBF measurements during median nerve stimulation (MNS) and compared GLM analysis with independent component analysis (ICA) for identifying the spatial, temporal and metabolic properties of responses in the primary sensorimotor cortex (S1/M1), and in the default mode (DMN) and fronto-parietal (FPN) networks. Excellent spatial and temporal agreement was observed between the positive BOLD and CBF responses to MNS detected by GLM and ICA in contralateral S1/M1. Values of the change in cerebral metabolic rate of oxygen consumption (δ%CMRO2) and the δ%CMRO2/δ%CBF coupling ratio were highly comparable when using either GLM analysis or ICA to extract the contralateral S1/M1 responses, validating the use of ICA for estimating changes in CMRO2. ICA identified DMN and FPN network activity that was not detected by GLM analysis. Using ICA, spatially coincident increases/decreases in both BOLD and CBF signals to MNS were found in the FPN/DMN respectively. Calculation of CMRO2 changes in these networks during MNS showed that the δ%CMRO2/δ%CBF ratio is comparable between the FPN and S1/M1 but is larger in the DMN than in the FPN, assuming an equal value of the parameter M in the DMN, FPN and S1/M1. This work suggests that metabolism-flow coupling may differ between these two fundamental brain networks, which could originate from differences between task-positive and task-negative fMRI responses, but might also be due to intrinsic differences between the two networks.
| Original language | English |
|---|---|
| Pages (from-to) | 111-121 |
| Number of pages | 11 |
| Journal | NeuroImage |
| Volume | 99 |
| Early online date | 23 May 2014 |
| DOIs | |
| Publication status | Published - 1 Oct 2014 |
Funding
We thank the Medical Research Council (MRC), Engineering and Physical Science Research Council ( EPSRC ) and University of Nottingham for funding this research. Grants: G0901321 , EP/F023057/1 , EP/J006823/1 . KJM was supported by a University of Nottingham Mansfield Fellowship and Anne McLaren Fellowship; SDM was funded by an EPSRC Fellowship ( EP/I022325/1 ) and a Birmingham Fellowship.
| Funders | Funder number |
|---|---|
| Medical Research Council | G0901321 |
| Engineering and Physical Sciences Research Council | EP/F023057/1, EP/J006823/1, EP/I022325/1 |
| University of Nottingham |
