Fractal analysis of spontaneous fluctuations of the BOLD signal in rat brain

Analysis of task-evoked fMRI data ignores low frequency fluctuations (LFF) of the resting-state the BOLD signal, yet LFF of the spontaneous BOLD signal is crucial for analysis of resting-state connectivity maps. We characterized the LFF of resting-state BOLD signal at 11.7T in alpha-chloralose and domitor anesthetized rat brain and modeled the spontaneous signal as a scale-free (i.e., fractal) distribution of amplitude power (vertical bar A vertical bar(2)) across a frequency range (f) compatible with an vertical bar A(f)vertical bar(2) proportional to 1/f(beta) model where beta is the scaling exponent (or spectral index). We compared beta values from somatosensory forelimb area (S1FL), cingulate cortex (CG), and caudate putamen (CPu). With alpha-chloralose, S1FL and CG beta values dropped from similar to 0.7 at in vivo to similar to 0.1 at post mortem (p<0.0002), whereas CPu beta values dropped from similar to 0.3 at in vivo to similar to 0.1 at post mortem (p<0.002). With domitor, cortical (S1FL, CG) beta values were slightly higher than with alpha-chloralose, while subcortical (CPu) beta values were similar with alpha-chloralose. Although cortical and subcortical beta values with both anesthetics were significantly different in vivo (p<0.002), at post mortem beta values in these regions were not significantly different and approached zero (i.e., range of -0.1 to 0.2). Since a water phantom devoid of susceptibility gradients had a beta value of zero (i.e., random), we conclude that deoxyhemoglobin present in voxels post-sacrifice still impacts tissue water diffusion. These results suggest that in the anesthetized rat brain the LFF of BOLD signal at 11.7T follow a general 1/f(beta) model of fractality where beta is a variable responding to physiology. We describe typical experimental pitfalls which may elude detection of fractality in the resting-state BOLD signal. (C) 2011 Elsevier Inc. All rights reserved.