Layer-Specificity of Functional Connectivity Estimates with bSSFP fMRI
Poster No:
1908
Submission Type:
Late-Breaking Abstract Submission
Authors:
Simon Faßnacht1, Dana Ramadan1, Maria-Aradia Wilms2,3, Sebastian Mueller1, Denis Chaimow2,4, Rüdiger Stirnberg5, Philipp Ehses5, Klaus Scheffler6,7, Jonas Bause1, Romy Lorenz8,4
Institutions:
1Max Planck Institute for Biological Cybernetics, Tuebingen, Germany, 2Max Planck Institute for Biological Cybernetics, Tübingen, Baden-Württemberg, 3Berlin School of Mind and Brain, Humboldt-Universitaet zu Berlin, Berlin, Germany, 4Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany, 5German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany, 6Department for Biomedical Magnetic Resonance, University of Tübingen, Tübingen, Germany, 7 Department of Biomedical Magnetic Resonance, University of Tuebingen, Tuebingen, Germany, 8Max Planck Institute for Biological Cybernetics, Tübingen, Germany
First Author:
Co-Author(s):
Maria-Aradia Wilms
Max Planck Institute for Biological Cybernetics|Berlin School of Mind and Brain, Humboldt-Universitaet zu Berlin
Tübingen, Baden-Württemberg|Berlin, Germany
Max Planck Institute for Biological Cybernetics|Berlin School of Mind and Brain, Humboldt-Universitaet zu Berlin
Tübingen, Baden-Württemberg|Berlin, Germany
Denis Chaimow
Max Planck Institute for Biological Cybernetics|Max Planck Institute for Human Cognitive and Brain Sciences
Tübingen, Baden-Württemberg|Leipzig, Germany
Max Planck Institute for Biological Cybernetics|Max Planck Institute for Human Cognitive and Brain Sciences
Tübingen, Baden-Württemberg|Leipzig, Germany
Klaus Scheffler
Department for Biomedical Magnetic Resonance, University of Tübingen| Department of Biomedical Magnetic Resonance, University of Tuebingen
Tübingen, Germany|Tuebingen, Germany
Department for Biomedical Magnetic Resonance, University of Tübingen| Department of Biomedical Magnetic Resonance, University of Tuebingen
Tübingen, Germany|Tuebingen, Germany
Romy Lorenz
Max Planck Institute for Biological Cybernetics|Max Planck Institute for Human Cognitive and Brain Sciences
Tübingen, Germany|Leipzig, Germany
Max Planck Institute for Biological Cybernetics|Max Planck Institute for Human Cognitive and Brain Sciences
Tübingen, Germany|Leipzig, Germany
Late Breaking Reviewer(s):
Rosanna Olsen
Rotman Research Institute, Baycrest Academy for Research and Education
Toronto, Ontario
Rotman Research Institute, Baycrest Academy for Research and Education
Toronto, Ontario
Introduction:
Recent advancements in ultra-high field fMRI have made it possible to study neural activity at the level of cortical layers, something previously limited to invasive animal studies. This opens up unprecedented opportunities to explore the human functional connectome, allowing insights into directed communication pathways both within and between large-scale networks and individual brain regions. However, most layer-specific functional connectivity (FC) studies to date rely on T2*-weighted GE-BOLD imaging (e.g. [1]), which lacks the necessary spatial specificity to accurately resolve laminar connectivity. A major limitation of GE-BOLD are draining vein biases, which lead to exaggerated signal amplitudes in superficial layers and signal leakage across cortical depths [2], both of which may distort laminar FC estimates. To address these limitations, VASO fMRI has been established as a layer-specific acquisition method [3]. Another promising alternative is balanced steady-state free precession (bSSFP) fMRI, which offers higher SNR and avoids geometric distortions [4]. Simulations indicate that the functional contrast in bSSFP is mainly driven by intravascular signal contributions and therefore reduces biases from large draining vessels [5]. The theoretically expected higher specificity of bSSFP fMRI was recently further supported by a resting state study showing reduced cortical orientation dependence of the measured signal compared to GE-BOLD [6]. The present study evaluates the potential of bSSFP for investigating layer-resolved FC, focusing on its reliability and layer specificity compared to conventional GE-BOLD.
Methods:
This work utilizes resting-state data by [6] from 5 subjects with an isotropic voxel size of 1.1mm3 acquired at 9.4T with 3 fMRI sequences: GE-BOLD using both a 2D-EPI and 3D-EPI readout as well as bSSFP fMRI (Fig. 1A). All functional images underwent motion correction, distortion correction (except bSSFP), bandpass filtering, nuisance regression including global signal regression, scrubbing, and were registered to an anatomical MPRAGE. Cortical surfaces were reconstructed from MPRAGE data using a Freesurfer-based pipeline [7]. A surface-based registration to fs_LR space was computed [8], and surface coordinates were transformed into functional space. From these transformed gray matter surfaces, voxel-wise cortical depths were computed to delineate equivolume cortical layers. Reliability of layer-resolved Pearson's FC estimates were assessed using a split-half approach using parcels from [9] (Fig. 1B). In addition, intra-area laminar connectivity was assessed for the left motor cortex M1 (following [3]). Finally, a hubness analysis was conducted correlating each layer timeseries to the average parcel timeseries to determine laminar contributions (following [10]).
Results:
1. With ~13 min of cleaned (i.e., censored) data, both 2D and 3D-EPI show high layer-resolved split-half reliability, while bSSFP achieves moderate reliability (Fig. 1C).
2. Within the left motor cortex, intra-area laminar connectivity for both GE-BOLD sequences shows a visible bias towards superficial layers in line with the draining vein effect, while for bSSFP we see correlations in superficial as well as deep layers (Fig. 2A).
3. Hubness analysis indicates that superficial layers dominate the parcel time series in GE-BOLD, while bSSFP exhibits a more balanced layer distribution (Fig. 2B).
2. Within the left motor cortex, intra-area laminar connectivity for both GE-BOLD sequences shows a visible bias towards superficial layers in line with the draining vein effect, while for bSSFP we see correlations in superficial as well as deep layers (Fig. 2A).
3. Hubness analysis indicates that superficial layers dominate the parcel time series in GE-BOLD, while bSSFP exhibits a more balanced layer distribution (Fig. 2B).
Conclusions:
Our findings suggest that bSSFP is a viable alternative for investigating laminar resting-state FC, mitigating superficial biases introduced by draining veins. However, bSSFP exhibits lower reliability compared to GE-BOLD, with reliability estimates ~37% lower. This highlights the need for longer resting-state acquisitions when using bSSFP to achieve comparable reliability in FC estimates. Consequently, bSSFP fMRI holds promise for future dense sampling studies seeking to explore the human functional connectome at the level of cortical layers.
Modeling and Analysis Methods:
Connectivity (eg. functional, effective, structural)
fMRI Connectivity and Network Modeling 2
Novel Imaging Acquisition Methods:
BOLD fMRI 1
Keywords:
Cortical Layers
FUNCTIONAL MRI
HIGH FIELD MR
Other - Resting State
1|2Indicates the priority used for review
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