Patricia Pais-Roldán1, Seong Dae Yun1, Michael Schwerter1, and Jon N Shah1,2,3,4
1Forschungszentrum Jülich - INM-4, Jülich, Germany, 2Forschungszentrum Jülich - INM-11, Jülich, Germany, 3JARA-BRAIN, Aachen, Germany, 4RWTH Aachen University, Aachen, Germany
Synopsis
Cross-cortical interactions in the human brain remain
poorly understood and are often over-simplified as a 2-dimensional cortical
model in fMRI studies. To date, high-resolution fMRI has been limited to relatively
small brain slabs that cover particular areas of interest, providing fine
mapping of local circuits but precluding macroscale analysis. Here, an EPIK
sequence was used to measure the GE-BOLD signal from individual cortical layers
through most of the brain. The combination of high resolution (0.63 mm isotropic)
and large coverage fMRI enabled identification of long-distance neuronal
interactions that take place between particular cortical depths during
resting-state.
Introduction
The neocortex in the mammalian brain is
organized, in depth, into 6 well-defined histological layers. The way in which
the cortical neurons communicate with each other in the human brain (across
different depths and through different areas) remains largely unknown,
primarily due to a lack of non-invasive methods to sufficiently sample the
cortical mantle. However, recently, layer-based functional MRI (fMRI) has enabled
the investigation of inter-laminar behaviour within defined regions engaged in
particular tasks.1-3 Despite this advance, the limited brain
coverage of the existing high-resolution-fMRI schemes precludes the
investigation of large-scale neuronal cross-talk in the human cortex.
It has
been previously shown that EPIK can offer higher resolution with comparable
performance in identifying functional signals.4-9 Therefore, in
order to achieve high-resolution fMRI with near-whole-brain coverage, here an
EPIK-based sequence10-13 was optimised to provide submillimetre
isotropic resolution (0.63 mm3) with 123 slices to acquire resting-state
fMRI in a healthy volunteer. A novel layer-based analysis approach enabled
detection of depth-dependent connectivity on a macro-scale.Methods
In order to investigate potentially different
connectivity patterns across individual cortical layers, a resting-state
paradigm was employed, which enhances the spontaneous synchronous firing of
distant neuronal populations (i.e. resting-state networks). This brain state
differs from that induced during evoked fMRI studies, where the activation area
is well localised and, hence, a large field-of-view is often not required. In
contrast, resting-state fluctuations occur broadly and, therefore, whole-brain
coverage is a prerequisite for characterisation. Here, an EPIK sequence was employed
to acquire GE-BOLD images with 0.63 mm isotropic resolution and near whole-brain
coverage (Fig. 1A&C). The
achieved voxel size is comparable with that used in current layer-fMRI studies,
but the matrix size is significantly larger than the one reported in the
literature, which indicates that the proposed method covers a much larger FOV.
In total, 206 volumes were acquired in a 7T scanner (Siemens Magnetom Terra)
using the following parameters: TR/TE: 3500/22 ms, FOV = 210 × 210 mm2, matrix = 336 × 336 × 123
slices (0.625 × 0.625 × 0.63
mm3), partial Fourier = 5/8 and 3-fold in-plane/3-fold inter-plane
(multi-band) acceleration. Additionally, MP2RAGE data were acquired to perform
brain segmentation and to generate six surfaces between the outer and the inner
limit of the cortex (Fig. 1B) using
FreeSurfer. Pre-processing of the fMRI data was performed with SPM and AFNI, which
included the following steps: slice timing correction, realignment and
regression of 12 motion parameters in the magnitude-reconstructed images.
Additionally, the phase data of the fMRI scans, having undergone the same
pre-processing steps, were unwrapped in the temporal domain and regressed out
from the magnitude fMRI scans to partially correct for large-vein
contamination.14,15 The corrected fMRI scans were then mapped to the
6 MP2RAGE-derived surfaces. Seven ROIs were manually drawn, based on the
results of an independent component analysis (FSL), and the time courses of
individual vertices were averaged together per surface and per ROI. Power
spectrum analysis was computed to identify activity changes through the
different layers across the cortex. Additionally, eigenvector centrality
mapping16 was computed per surface, and a connectivity matrix was
generated including 84 clusters (7 ROIs × 6 surfaces × 2 cerebral hemispheres).Results
Spectral analysis of the signals acquired from
different cortical depths across distant regions revealed distinct activation
patterns through both cortical hemispheres (Fig. 2), with most ROIs exhibiting their maximum power in the upper
layers for nearly all frequency bands studied. In agreement with this, the
outer surface of the cortex presented a greater degree of centrality when
compared to deeper layers (Fig. 3). High-degree
correlation analysis identified particular connections between clusters located
at different depths and regions, especially, but not limited to, the
superficial layers (Fig. 4A&B),
thus, further demonstrating the heterogeneous behaviour of the cortex. Graph
analysis identified reliable intra- and inter-hemispheric connectivity
patterns, especially between the anterior frontal cortex and the visual cortex
(Fig. 4B), which verifies the
capabilities of high-resolution EPIK for whole-brain mapping.Discussion / conclusions
The presented results indicate evidence of a
depth-dependent orchestration of neuronal activity in the resting human brain.
An optimised version of EPIK enabled expansion of the boundaries of current
high-resolution fMRI to infer inter-laminae connectivity through the whole
cortex, adding a further dimension to the current resting-state fMRI. Analysis
of the data remains challenging due to the high computational demands and the
difficulty of achieving perfect whole-brain co-registration between the
functional and the anatomical images. However, taken together, our results
demonstrate the potential of the EPIK method to track neuronal oscillations
with layer specificity through the whole-brain.Acknowledgements
We thank Elke Bechholz for technical support and the fMRI volunteers for their excellent cooperation.References
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