Introduction

Layer-specific analysis of neuronal activity in the human brain using MRI can be difficult to perform because of restrictions imposed by available signal-to-noise ratio (SNR) and hardware limitations. However, ultra-high-field MRI scanners (≥ 7T) enable obtaining high-resolution functional images with submillimeter resolution and thus cortical depth sensitivity^1,2. In this study, we analyze laminar profiles in the primary visual cortex (V1) of human subjects using black and white-colored visual stimuli. This is motivated by a previous study where distinct layer activation differences were observed in primate V1 electrophysiology recordings³. We analyzed functional data acquired with a 7T human MRI scanner using voxel centroid mapping method, which calculates relative cortical depth of voxels, therefore accurately illustrating depth-dependent cortical laminar BOLD responses without the necessity of resampling functional data. The results from this study can help elucidate the underlying laminar-specific mechanisms in which visual objects with varying luminance are processed in the human visual cortex.

Materials and Methods

Functional data were acquired using a 7T whole-body scanner (Magnetom Terra, Siemens Healthineers, Erlangen, Germany) and a 32-Rx/1-Tx head coil (Nova Medical, Wilmington, MA, USA). Four healthy subjects were scanned (two subjects were scanned twice) pursuant to the procedures approved by the institutional review board.

Vendor-provided 2D echo-planar imaging (EPI) sequence with the following imaging parameters was used for functional data acquisition: 0.8 mm isotropic spatial resolution, 64 slices, TR/TE = 3000/29 ms, matrix size = 240 x 240, acceleration (phase⁴ x slice⁵) = 2 x 3. The anatomical data acquired with MP2RAGE sequence were distorted using a field map acquired with a double-echo gradient-recalled echo (GRE) sequence to match the distortion of the EPI images. FSL software package was used for motion-correction and co-registration of functional data^6,7,8.

For every scan session, four functional datasets were acquired with visual stimulation. Each dataset comprised of 12 task periods with simple stimuli: a white or black dot appearing for 21 seconds in the first quadrant (upper right corner) of the screen, as shown in Figure 1. Two datasets were acquired with on/off stimulation blocks. The other two datasets were acquired with continuous stimulation with no interleaved rest periods. For both stimulation paradigms, the dot stimuli made continuous random walk motion (restricted within an invisible wall stretching 5% of the width and the height of screen from the center of the first quadrant) with the intention of reducing adaptation during the task periods. Subjects were instructed to fixate their eyes on a small cross located at the center of the screen and press a button whenever its shade changed from bright red to dark red to promote attention.

Voxel centroid mapping method was used for estimating the relative cortical depth of every voxel in the ROI. Without resampling the functional data or the activation map, each voxel’s center coordinate is “mapped,” defining its relative distance between the GM-CSF and the GM-WM borders. This practice can help perform laminar activation analysis with minimum smoothing of data and enable plotting results from ROIs in multiple slices across different subjects, taking full advantage of high spatial resolution available in ultra-high-field MRI scanners. Figure 2 illustrates an example of single-slice masking and cortical depth calculation.

Results and Discussion

Figure 3 shows cortical depth-dependent time-course intensity plots of masked voxels (B and D). These match well with the stimulation onsets and average time-course intensity of all activation regions (A and C). Although V1 gray matter thickness is limited to ~2mm, covering many voxels with distinct cortical depth values helped divide the cortical depth into 10 bins and average intensity profiles per bin, resulting in an effective spatial resolution greater than the imaging resolution without data resampling.

Figure 4 shows the time-course intensity of task blocks averaged for black and white dot task periods. The subtracted time-course data (normalized) of each stimulus shows the black dot response delayed by 1~2 TRs compared to the white dot response. This behavior was observed again more clearly with continuous stimulation.

BOLD activation induced by black dot was greater compared to the activation by the white dot. As shown in Figure 5, block stimulation paradigm yielded greater activation for both black and white dot stimuli overall, having maximum activation near the gray matter surface. The voxel-wise activation averaged per 10 cortical depth bins reached 6% and 5%, for black and white dots, respectively. The data acquired with continuous stimulation, however, showed peak activation near the middle layers, where average activation per cortical depth bin neared 2.5% and 1.5%, for black and white dots, respectively. The differences in magnitude of white dot and black dot-induced activations were more distinct for the data acquired with continuous stimulation. Additional data acquisition is planned with data analysis ongoing.

Conclusion

Data shown here indicate low luminance (black dot) visual stimulus inducing a greater BOLD activation overall in V1. This aligns well with the findings from electrophysiology recordings in macaque V1. Forthcoming inter-subject analysis with additional data can help define black-or-white dominant layers in human V1.

Acknowledgements

This work was supported by the Institute of Basic Science under grant IBS-R015-D1.