This is the first fMRI study that used phase information to evaluate vascular effects on activation patterns across subjects. The major finding of the study is that group analyses of brain activation may include significant macrovascular contribution. To minimize this contribution we propose a method that is fully compatible with the standard GLM.
The phase of the BOLD-fMRI signal is sensitive to small magnetic field variations. We have demonstrated that while the phase of the signal is strongly driven by global effects (local shimming), the use of a phase reference removes the unwanted global field effects allowing mapping very weak magnetic fields (~ 10−9
Tesla) (Tomasi and Panepucci 1999
; Tomasi et al. 1998
). In the present study, we demonstrated that the “relative-phase” (i.e. the phase change with the first time point) of the BOLD-fMRI signal is not wrapped by global field effects and is modulated by the task, allowing whole brain mapping of task-related phase changes with high precision (Δψ
> 0.5°; ΔB = Δ ψ
/ γTE > 1.3E-9 Tesla).
The (left lateralized) occipital and prefrontal ψ
–activation clusters ( “Phase”) could be distant (one or more cm away) from the true (neuronal) activation sites (Ogawa et al. 1998
), and reflect only a fraction of the common neurovasculature (large draining veins, such as the branches of the middle or the superior cerebral veins) across subjects. Note that the ψ
–signal depends on vein orientation [θ
; Eq (2)
], blood flow, and partial volume effects; therefore large veins would not have been mapped in “Phase”. Indeed, the association of the ventral prefrontal ψ
–deactivation and subject motion (pitch rotation angle) suggest that phase changes in this region may reflect motion-related changes of the magnetic field distribution. Our findings on ψ
–deactivation are further supported by previous studies that demonstrated motion-related changes in T2*-relaxation near the sinus cavity (Caparelli et al. 2005
). Therefore, small but stimulus-correlated motion of the head in the strong non-linear magnetic field gradient produced by the sinus cavity may have resulted in a synchronous modulation of ψ
in this region. Thus ρ
–activation clusters in or near these regions may include unwanted contributions from the vascular pool or be motion related.
The proposed filtering method is based on 1) the detection of voxels with small (1.5 ° < ψ < 20 ° or 4° < ψ < 20°) but significant (P < 0.001, uncorrected) ψ-changes in the whole brain, and 2) the elimination of the time-dependent signal modulation at those voxels in the ρ–time series; this elimination is carried out at early stages of image postprocessing (before spatial normalization and smoothing) to prevent further dispersion of the ψ–point s pread function.
The lower significance of filtered activation clusters in the superior parietal, prefrontal and occipital cortices ( “Filtered”) compared to the corresponding unfiltered ( “Unfiltered”) clusters also suggest significant macrovascular contributions in these regions. Specifically, blood oxygenation changes in the superior cerebral veins and their pial and cortical branches may have contributed to the ρ
–signal. These veins drain the superior, lateral, and medial surfaces of the brain and are mostly perpendicularly oriented to the scanners’ magnetic field. Consequently, the task-dependent modulation of deoxyhemoglobin concentration in these veins could have modulated the magnetic field in both the microvascular and macrovascular pools in these cortices. The differential “Filtered > Unfiltered” activation pattern depicts brain regions having significant ψ
–, and ρ
–effects across subjects, including the superior parietal cortex, medial frontal, middle, and inferior frontal gyri. Therefore the middle cerebral vein, which begins on the lateral surface of the PFC and runs along the lateral cerebral fissure (Huettel et al. 2004
), and its pial and cortical branches, could have also contributed to the BOLD-fMRI signal during working memory tasks.
Hence, the commonly observed large activation in the superior prefrontal as well as parietal regions in fMRI studies using working memory and other cognitive tasks may not reflect large recruitment of network resources in these regions during the tasks; activation in these regions could include significant macrovascular contributions reflecting neuronal activation at remote locations. Other activated regions (basal ganglia, and cerebellum), however, did not show a stimulus-dependent modulation of the phase component of the MRI signal; therefore brain activation in these regions might not include significant macrovascular contributions and be more closely located to the sites of neuronal activation. This study further demonstrates that the phase component of complex BOLD-fMRI datasets can be used to produce activation patterns reflecting dynamic vascular changes in the brain.