Poster No:
2554
Submission Type:
Abstract Submission
Authors:
Alessandra Pizzuti1, Omer Faruk Gulban1,2, Laurentius (Renzo) Huber3, Judith Peters1, Rainer Goebel1
Institutions:
1Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht, Netherland, 2Brain Innovation, Maastricht, Netherlands, 3Functional MRI Core Facility, National Institute of Mental Health, Bethesda, MD
First Author:
Alessandra Pizzuti
Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience
Maastricht, Netherland
Co-Author(s):
Omer Faruk Gulban, Ph.D.
Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience|Brain Innovation
Maastricht, Netherland|Maastricht, Netherlands
Judith Peters
Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience
Maastricht, Netherland
Rainer Goebel
Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience
Maastricht, Netherland
Introduction:
Ultra-high field fMRI (≥7 Tesla) enables sub-millimeter investigation of human conscious perception. Prior studies dissociated perceptual interpretation of visual motion in the motion sensitive area (hMT+) [1]. Yet, how perceived motion is constructed and modulated in the visual stream is unknown. Our 7T fMRI study explores how motion perception is orchestrated in visual areas (V1, V2, V3 and hMT+) and their laminar connectivity profiles. Using a bistable stimulus (physical and ambiguous motion quartet) [1], we dissociate feedforward from feedback signal integration and their neural correlates. Our results from V1 and hMT+ show differential laminar profiles for the two stimulus conditions.
Methods:
The ambiguous quartet induced perception of horizontal or vertical movement through blinking squares at diagonally opposite corners (80s), alternating with a flicker condition (16s). Participants indicated percepts via a MR-compatible button box. In the physical quartet, squares moved along the same horizontal or vertical paths as targeted during the ambiguous motion. Five healthy participants underwent two 2-hour sessions using Siemens MAGNETOM Plus 7T at Scannexus (Maastricht, Netherlands). Per participant, we collected an MP2RAGE [4] (0.7 iso mm), a hMT+ functional localizer, 2 retinotopic mapping runs and 12 runs (12 min each) for the motion quartet stimulus (6 physical) using 2D gradient-echo (GE)-BOLD (0.8 iso mm, TR=2s) [5]. BOLD fMRI data (bilateral coverage) underwent preprocessing: slice time correction [6], motion correction [6], distortion correction [7], high-pass filter (5 cycles) [6] and co-registered to the anatomical images via boundary-based registration [6]. Two subjects were excluded due to motion. Anatomical images were bias field corrected [8], skull-stripped [7], upsampled to 0.35 iso mm. White (WM) and gray matter (GM) segmentation was performed [6] and manually corrected in ITK-SNAP [8]. GM cortical layers were defined by the equi-volume principle [9]. WM surfaces were reconstructed [6] and used to define the regions of interest (ROI). V1, V2, V3 ROIs were delineated using polar angle and eccentricity maps [10]. hMT+ ROI was defined using a separate visual motion localizer. A multi-run general linear model [6] characterized functional responses to physical and ambiguous conditions. Horizontal and vertical clusters (top 10% t-values, from the contrast: horizontal > vertical) in V1 and hMT+ were propagated to cover the whole cortical depth [9] and visualized on flattened GM [9]. Only voxels maintaining preference (horizontal or vertical) between two conditions (congruent voxels) were considered for laminar analysis (t-maps are upsampled to 0.35 iso mm).
Results:
Although our ambiguous stimulus elicits a robust motion percept, fMRI responses are consistently lower compared to the physical condition, suggesting reduced brain response without sensory input. In the physical condition, V1 shows a stronger response than hMT+ (Fig.1 B, F), aligning with its expected retinotopic organization. Conversely, fMRI modulation is similar across ROIs in the ambiguous condition (Fig.1-C, G). hMT+ exhibits a higher percentage of congruent voxels between conditions (64%) than V1 (46%) on average. Cortical depth analysis reveals a consistent V1 middle layer peak in the physical condition, hinting at deep layer modulation in the ambiguous condition (Fig.1-C,D and Fig2-A). Laminar profiles in hMT+ lack a clear pattern across participants (Fig.2), we observe a demodulation of the middle layer in only one participant (Fig.1-L).
Conclusions:
In conclusion, our high-resolution BOLD fMRI study disentangles feedforward and feedback modulation in V1. Preliminary results confirm feedforward influence on the middle layer and feedback on the deep layers during motion perception, aligning with previous V1 studies [3]. Further analysis is crucial to address the draining vein effect, conduct statistical inference on layer profiles, and explore laminar behavior in V2 and V3.
Modeling and Analysis Methods:
Connectivity (eg. functional, effective, structural)
Novel Imaging Acquisition Methods:
BOLD fMRI 2
Perception, Attention and Motor Behavior:
Perception: Visual 1
Keywords:
Consciousness
Cortical Columns
Cortical Layers
FUNCTIONAL MRI
HIGH FIELD MR
MRI
Perception
Vision
1|2Indicates the priority used for review
Provide references using author date format
[1] Schneider, M., Kemper, V. G., Emmerling, T. C., De Martino, F., & Goebel, R. (2019). Columnar clusters in the human motion complex reflect consciously perceived motion axis. Proceedings of the National Academy of Sciences of the United States of America, 116(11), 5096–5101. https://doi.org/10.1073/pnas.1814504116
[2] Alessandra Pizzuti, Laurentius (Renzo) Huber, Omer Faruk Gulban, Amaia Benitez-Andonegui, Judith Peters, Rainer Goebel, Imaging the columnar functional organization of human area MT+ to axis-of-motion stimuli using VASO at 7 Tesla, Cerebral Cortex, Volume 33, Issue 13, 1 July 2023, Pages 8693–8711, https://doi.org/10.1093/cercor/bhad151
[3] Peter Kok, Lauren J. Bains, Tim van Mourik, David G. Norris, Floris P. de Lange, Selective Activation of the Deep Layers of the Human Primary Visual Cortex by Top-Down Feedback, Current Biology, Volume 26, Issue 3, 2016, Pages 371-376, ISSN 0960-9822, https://doi.org/10.1016/j.cub.2015.12.038.
[4] Marques, J. P. et al. (2010) ‘MP2RAGE, a self bias-field corrected sequence for improved segmentation and T1-mapping at high field’, NeuroImage, 49(2), pp. 1271–1281. doi: 10.1016/j.neuroimage.2009.10.002.
[5] Moeller S, et al. (2010) Multiband multislice GE-EPI at 7 tesla, with 16-fold acceleration using partial parallel imaging with application to high spatial and temporal whole-brain FMRI. Magnetic Resonance in Medicine.
[6] Goebel, R. (2012) ‘BrainVoyager - Past, present, future’, NeuroImage, 62(2), pp. 748–756. doi: 10.1016/j.neuroimage.2012.01.083.
[7] Smith, S. M. et al. (2004) ‘Advances in functional and structural MR image analysis and implementation as FSL’, in NeuroImage. doi: 10.1016/j.neuroimage.2004.07.051.
[8] Yushkevich, P. A. et al. (2006) ‘User-guided 3D active contour segmentation of anatomical structures: Significantly improved efficiency and reliability’, NeuroImage, 31(3), pp. 1116–1128. doi: 10.1016/j.neuroimage.2006.01.015.
[9] Huber, L. (Renzo) R. et al. (2021) ‘LayNii: A software suite for layer-fMRI’, NeuroImage, 237(May), p. 118091. doi: 10.1016/j.neuroimage.2021.118091.
[10] Senden M, Reithler J, Gijsen S, Goebel R (2014) Evaluating Population Receptive Field Estimation Frameworks in Terms of Robustness and Reproducibility. PLOS ONE 9(12): e114054. https://doi.org/10.1371/journal.pone.0114054