Wouter Schellekens1,2, Jonathan Winawer3, and Natalia Petridou4
1Psychiatry, Radboud UMC, Nijmegen, Netherlands, 2Radiology, UMC Utrecht, Utrecht, Netherlands, 3Department of psychology, NYU, New York, NY, United States, 4UMC Utrecht, Utrecht, Netherlands
Synopsis
Keywords: Blood Vessels, fMRI (task based), Neurovascular coupling
Motivation: We aimed to unravel the intricate relationship between neuronal metrics and vascularization in human visual cortex, addressing the need for a deeper understanding of these factors' impact on fMRI data.
Goal(s): Our study sought to determine if differences exist in pRF sizes between micro- and macro-vascular compartments and the influence of extra- and intra-vascular effects.
Approach: We obtained pRF estimates across cortical depth using different fMRI scan sequences (SE/GE) at varying field strengths (7T/3T).
Results: While our findings confirmed typical pRF size trends and vascularization-dependent amplitude effects across cortical depth, we did not find that vascularization or magnetic field strength affected pRF sizes.
Impact: This study's findings challenge the conventional
understanding of how vascularization affects neuronal metrics in functional
brain imaging. The research underscores the complexity of neurovascular
interactions and their implications for the interpretation of fMRI data.
Introduction
Functional magnetic resonance imaging (fMRI) is an essential
method for studying human brain function. However, fMRI does not reflect
neuronal activity directly, but rather represents a complex process referred to
as neurovascular coupling1.
Consequently, vascular properties (e.g. vessel size) influence fMRI
measurements. The current study investigates to what extent neuronal metrics
such as population Receptive Field (pRF) measurements in visual cortex2,3 are
influenced by non-neuronal vascularization properties. By using spin-echo (SE)
and gradient-echo (GE) BOLD-fMRI, we capture micro-vascular and macro-vascular
weighted BOLD signals. Micro-vascular signals better reflect neuronal activity,
while macro-vascular signals are increasingly affected by large (draining)
veins towards the pial surface4–6. BOLD-fMRI
at 7T emphasizes extra-vascular effects, while 3T includes intra- and
extra-vascular influences7. Therefore,
BOLD-fMRI at 7T is expected to offer a more precise representation of the locus
of neural activity compared to 3T measurements. We predict smaller pRF sizes in
micro-vascular compartments, particularly in superficial cortical layers.
Additionally, we anticipate larger pRF sizes at 3T compared to 7T due to the
additional intra-vascular effects, enhancing our understanding of neurovascular
interactions.Methods
Ten healthy volunteers (mean age = 22.9, F = 5) participated in 3
fMRI sessions that differed with respect to field strength (7T / 3T) and scan
sequence (SE / GE): 7TSE (voxel size: 1.5 mm isotropic), 7TGE (voxel size: 1.0
mm isotropic), and 3TGE (voxel size: 2.0 mm isotropic). The repetition time
(TR) was 0.85 s for each session and the field of view was oriented in a way
that matched the coverage of the occipital lobe in all sessions. During each
session, 2 retinotopic visual field mapping experiments were conducted,
consisting of 250 dynamics each. Cortical depth masks were created using LayNii
software8. Two-dimensional pRF analysis was
performed, resulting in estimated amplitude, pRF center (polar angle &
eccentricity), and pRF size metrics (Figure 1). Voxels with a significant pRF
goodness-of-fit statistic were selected and were assigned an ROI (V1, V2 or V3)
and cortical depth label (deep, middle, superficial). Significance of fixed
effects (fMRI-session, eccentricity representation, ROI, and cortical depth
bin) on the estimated BOLD amplitude and pRF size was assessed using linear
mixed effect models.Results
We confirmed the typical increases in pRF size across eccentricity
representations (Z=8.32; β=0.268;
95%CI=[.205,.331]), and across the visual hierarchy from V1 to V2 and V3 (Z=3.47;
β=0.089; 95%CI=[.039,.140]). However,
we did not observe a difference in pRF size between the 3 fMRI sessions (Z=0.64;
β=0.040; 95%CI=[-.161,.081]). Furthermore,
we did not observe the previously reported smaller pRF sizes for middle
cortical layers9 (Figure 2; Z=0.78; β=0.048; 95%CI=[-.084,.180]). However, we did
observe the typical BOLD amplitude increase across cortical depth during 7TGE10 (Z=7.88; β=0.778;
95%CI=[.585,.972]), which was not seen for 7TSE (Figure 3; Z=1.91; β=0.121; 95%CI=[-.003,.245]). Generally, the
BOLD amplitude during 7TGE was consistently larger compared to the other
sessions (Z=10.76; β=2.145;
95%CI=[1.754,2.536]).Discussion
In this study, we utilized pRF size as a neuronal metric that has
been verified independently of fMRI and across species11,12. We hypothesized that pRF sizes would
depend on vascularization in combination with magnetization properties.
However, our results cannot confirm such interpretation. Whilst typical pRF
size effects -such as the pRF size increase across eccentricity representation
and visual hierarchy3- can be confirmed, we did not observe
a difference in pRF size across scan sessions. Therefore, pRF sizes were not
dependent on vascular compartment size or intra- / extra-vascular magnetization
effects. Additionally, we did not observe pRF size differences across cortical
depth, neither for micro- or macro-vascular compartments. Possibly, our study
lacked the required spatial resolution to detect these cortical depth-dependent
effects. However, we did observe a strong BOLD amplitude increase across
cortical depth for 7TGE, which was not observed for 7TSE, indicative of
sufficient cortical depth-dependent sensitivity. A putative explanation for
these findings is that fMRI pRF estimates do not reflect neuronal tuning
functions that are propagated through neurovascular interactions, but rather
reflect (complex) channel response functions that not necessarily linearly relate
to neuronal tuning curves13.Conclusion
This study explored the influence of vascularization on pRF
size estimates in the human visual cortex. Our results suggest that pRF sizes
do not vary significantly with vascular compartment size or magnetic field
strength. While limitations in spatial resolution may account for some
findings, the strong BOLD amplitude increase in 7TGE hints at a complex channel
response rather than a direct reflection of neuronal tuning curves. This
research enhances our understanding of the interplay between neurovascular factors
and neuronal metrics in fMRI studies of human brain function.Acknowledgements
This work was supported by the National Institute Of Mental Health of the National Institutes of Health under Award Number R01MH111417References
1. Huneau, C., Benali, H. & Chabriat,
H. Investigating human neurovascular coupling using functional neuroimaging: A
critical review of dynamic models. Front. Neurosci. 9, 1–12
(2015).
2. Dumoulin, S. O. & Wandell, B. A.
Population receptive field estimates in human visual cortex. Neuroimage 39,
647–60 (2008).
3. Wandell, B. A. & Winawer, J.
Computational neuroimaging and population receptive fields. Trends Cogn.
Sci. 19, 349–357 (2015).
4. Uludaǧ, K., Müller-Bierl, B. & Uǧurbil,
K. An integrative model for neuronal activity-induced signal changes for
gradient and spin echo functional imaging. Neuroimage 48, 150–165
(2009).
5. Zhao, F., Wang, P. & Kim, S. G.
Cortical Depth-Dependent Gradient-Echo and Spin-Echo BOLD fMRI at 9.4T. Magn.
Reson. Med. 51, 518–524 (2004).
6. Siero, J. C. W. et al. BOLD
Specificity and Dynamics Evaluated in Humans at 7 T: Comparing Gradient-Echo
and Spin-Echo Hemodynamic Responses. PLoS One 8, 1–8 (2013).
7. Uludağ, K. & Blinder, P. Linking
brain vascular physiology to hemodynamic response in ultra-high field MRI. Neuroimage
168, 279–295 (2018).
8. Huber, L. (Renzo) R. et al.
LayNii: A software suite for layer-fMRI. Neuroimage 237, 118091
(2021).
9. Fracasso, A., Dumoulin, S. O. &
Petridou, N. Point-spread function of the BOLD response across columns and
cortical depth in human extra-striate cortex. Prog. Neurobiol. 102034
(2021) doi:10.1016/j.pneurobio.2021.102034.
10. Van Dijk, J. A., Fracasso, A., Petridou,
N. & Dumoulin, S. O. Linear systems analysis for laminar fMRI: Evaluating
BOLD amplitude scaling for luminance contrast manipulations. Sci. Rep. 10,
1–15 (2020).
11. Van Den Bergh, G., Zhang, B., Arckens,
L. & Chino, Y. M. Receptive-field properties of V1 and V2 neurons in mice
and macaque monkeys. J. Comp. Neurol. 518, 2051–2070 (2010).
12. Dräger, U. C. Receptive fields of single
cells and topography in mouse visual cortex. J. Comp. Neurol. 160,
269–289 (1975).
13. Gardner, J. L. & Merriam, E. P.
Population Models, Not Analyses, of Human Neuroscience Measurements. Annu.
Rev. Vis. Sci. 7, 225–255 (2021).