Nitric oxide (NO) is a key signalling molecule in the regulation of cerebral blood flow. This review summarises current evidence regarding the role of NO in the regulation of cerebral blood flow at rest, under physiological conditions, and after brain injury, focusing on subarachnoid haemorrhage, traumatic brain injury, and ischaemic stroke and following cardiac arrest. We also review the role of NO in the response to hypoxic insult in the developing brain. NO depletion in ischaemic brain tissue plays a pivotal role in the development of subsequent morbidity and mortality through microcirculatory disturbance and disordered blood flow regulation. NO derived from endothelial nitric oxide synthase (eNOS) appears to have neuroprotective properties. However NO derived from inducible nitric oxide synthase (iNOS) may have neurotoxic effects. Cerebral NO donor agents, for example sodium nitrite, appear to replicate the effects of eNOS derived NO, and therefore have neuroprotective properties. This is true in both the adult and immature brain. We conclude that these agents should be further investigated as targeted pharmacotherapy to protect against secondary brain injury.

The brainstem is directly involved in controlling blood pressure, respiration, sleep/wake cycles, pain modulation, motor, and cardiac output. As such it is of significant basic science and clinical interest. However, the brainstem’s location close to major arteries and adjacent pulsatile cerebrospinal fluid filled spaces, means that it is difficult to reliably record functional magnetic resonance imaging (fMRI) data from. These physiological sources of noise generate time varying signals in fMRI data, which if left uncorrected can obscure signals of interest. In this Methods Article we will provide a practical introduction to the techniques used to correct for the presence of physiological noise in time series fMRI data. Techniques based on independent measurement of the cardiac and respiratory cycles, such as retrospective image correction (RETROICOR, Glover et al., 2000), will be described and their application and limitations discussed. The impact of a physiological noise model, implemented in the framework of the general linear model, on resting fMRI data acquired at 3 and 7 T is presented. Data driven approaches based such as independent component analysis (ICA) are described. MR acquisition strategies that attempt to either minimize the influence of physiological fluctuations on recorded fMRI data, or provide additional information to correct for their presence, will be mentioned. General advice on modeling noise sources, and its effect on statistical inference via loss of degrees of freedom, and non-orthogonality of regressors, is given. Lastly, different strategies for assessing the benefit of different approaches to physiological noise modeling are presented.

Purpose:To estimate the importance of respiratory and cardiac effects on signal variability found in functional magnetic resonance imaging data recorded from the brainstem. Materials and Methods:A modified version of the retrospective image correction (RETROICOR) method (Glover et al, [2000] Magn Reson Med 44:162-167) was implemented on resting brainstem echo-planar imaging (EPI) data in 12 subjects. Fourier series were fitted to image data based on cardiac and respiratory recordings (pulseoximetry and respiratory turbine), including multiplicative terms that accounted for interactions between cardiac and respiratory signals. F-tests were performed on residuals produced by regression analysis. Additionally, we evaluated whether modified RETROICOR improved detection of brainstem activation (in 11 subjects) during a finger opposition task. Results:The optimal model, containing three cardiac (C) and four respiratory (R) harmonics, and one multiplicative (X) term, "3C4R1X," significantly reduced signal variability without overfitting to noise. The application of modified RETROICOR to activation data increased group Z-statistics and reduced putative false-positive activation. Conclusion:In addition to cardiac and respiratory effects, their interaction was also a significant source of physiological noise. The modified RETROICOR model improved detection of brainstem activation and would be usefully applied to any study examining this brain region.