Continuous stimulation and fine-scale contrast reduce superficial bias in laminar BOLD fMRI
Poster No:
1893
Submission Type:
Abstract Submission
Authors:
Chencan Qian1, Peng Zhang1
Institutions:
1Institute of Biophysics, Chinese Academy of Sciences, Beijing, China
First Author:
Co-Author:
Introduction:
Gradient-echo BOLD fMRI often suffers from superficial bias due to the draining effect of pial and penetrating veins (Yacoub, 2019), obscuring the true depth profile of neural activity. CBV-based methods like VASO improve spatial specificity (Huber, 2017), though with trade-offs in sensitivity and temporal resolution. Seeking for better experiment design and analysis strategies (Kay, 2020) that mitigate the superficial bias while leveraging the high SNR of gradient-echo EPI is crucial for a broader application of layer fMRI. Here, we demonstrate that a continuous stimulation paradigm combined with fine-scale differential contrast analysis can reduce superficial bias in gradient-echo BOLD responses, enabling more accurate layer profile estimation.
Methods:
We re-analyzed 7T gradient-echo fMRI data (0.8 mm isotropic resolution, 12 participants) from our previous study (Qian, 2023), and compared superficial bias in different components of the BOLD response. The experiment involved monocular presentation of a flickering checkerboard to either the left (LE) or right eye (RE, Fig.1a) in alternating 24 s blocks. Blank intervals (24 s) only appeared at the beginning and end of each run (Fig.1b). In this so-called "continuous stimulation paradigm", each hypercolumn in V1 is hypothesized to be continuously driven and thus maintain a steady-state activation in the macrovasculature, which can be canceled out by a fine-scale contrast between ocular dominance columns within the hypercolumn. The resulting differential response reflects more of the microvasculature and may exhibit less superficial bias.
To verify this hypothesis, we first performed a general linear model analysis to identify LE- and RE-biased voxels across cortical layers in V1, and extracted the mean response time course pooling voxels and runs (Fig.2a). Vessel contaminated voxels were column-wise excluded. Two metrics were then calculated: (1) the mean activation of the hypercolumn, defined as the average response of LE and RE voxels ((LE+RE)/2, Fig.2b), and (2) the fine-scale differential contrast ((LE-RE)/2, Fig.2c), reflecting ocular selectivity. Responses were compared between the first stimulation block (initial response, 4 to 24 s after stimulus onset) and subsequent blocks (steady-state response, third to the final block). The response of the first block after the initial blank interval was assumed to be similar to that in a non-continuous stimulation condition where hypercolumns experience interleaved activation and rest. Laminar profiles were assessed for both metrics and time windows.
To verify this hypothesis, we first performed a general linear model analysis to identify LE- and RE-biased voxels across cortical layers in V1, and extracted the mean response time course pooling voxels and runs (Fig.2a). Vessel contaminated voxels were column-wise excluded. Two metrics were then calculated: (1) the mean activation of the hypercolumn, defined as the average response of LE and RE voxels ((LE+RE)/2, Fig.2b), and (2) the fine-scale differential contrast ((LE-RE)/2, Fig.2c), reflecting ocular selectivity. Responses were compared between the first stimulation block (initial response, 4 to 24 s after stimulus onset) and subsequent blocks (steady-state response, third to the final block). The response of the first block after the initial blank interval was assumed to be similar to that in a non-continuous stimulation condition where hypercolumns experience interleaved activation and rest. Laminar profiles were assessed for both metrics and time windows.
·Figure1. Visual stimulus and experiment procedure for continuous stimulation.
Results:
The initial response following stimulus onset was strong but less selective. The mean response for the two eyes in the first block was twice as strong as those in the steady-state (Fig.2b/d). Both LE- and RE-biased voxels were strongly activated in the first block although only one eye was stimulated, and the differential contrast was significantly smaller compared to steady-state blocks (Fig.2c/d), suggesting that macrovasculature may play a dominant role in shaping the initial response.
During continuous stimulation, the steady-state mean response ((LE+RE)/2) showed a marked reduction in superficial bias compared to the initial response (Fig.2d, purple). In addition, the fine-scale differential response peaked in middle layers, reflecting the expected laminar profile of neural selectivity (Fig.2d, orange). The improved laminar specificity was most robust in the steady-state response, but already evident in the very first block.
During continuous stimulation, the steady-state mean response ((LE+RE)/2) showed a marked reduction in superficial bias compared to the initial response (Fig.2d, purple). In addition, the fine-scale differential response peaked in middle layers, reflecting the expected laminar profile of neural selectivity (Fig.2d, orange). The improved laminar specificity was most robust in the steady-state response, but already evident in the very first block.
·Figure2. Initial and steady-state phases of the mean response and fine-scale differential contrast in V1.
Conclusions:
Continuous stimulation paradigms and fine-scale differential contrast can reduce superficial bias in gradient-echo BOLD activity, possibly by avoiding to sample the large initial transient in the macrovascular response and canceling it out in the differential signal to highlight changes in the microvasculature. These findings demonstrate that it is possible to achieve reliable laminar profiles with gradient-echo BOLD, enhancing its applicability for layer fMRI studies.
Modeling and Analysis Methods:
Activation (eg. BOLD task-fMRI) 2
Methods Development
Neuroanatomy, Physiology, Metabolism and Neurotransmission:
Microcircuitry and Modules
Novel Imaging Acquisition Methods:
BOLD fMRI 1
Perception, Attention and Motor Behavior:
Perception: Visual
Keywords:
Cortical Columns
Cortical Layers
Design and Analysis
FUNCTIONAL MRI
HIGH FIELD MR
Vision
Other - Vasculature
1|2Indicates the priority used for review
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Provide references using APA citation style.
Kay, K. (2020). A temporal decomposition method for identifying venous effects in task-based fMRI. Nature Methods.
Koopmans, P. J. (2019). Strategies and prospects for cortical depth dependent T2 and T2* weighted BOLD fMRI studies. NeuroImage.
Qian, C. (2023). Hierarchical and fine-scale mechanisms of binocular rivalry for conscious perception. bioRxiv.