Response of the right hemisphere to the binocular loss of the central vision – FBA & pRF results
Poster No:
2083
Submission Type:
Late-Breaking Abstract Submission
Authors:
Kamil Lipinski1, Marco Ninghetto2, Kamil Szulborski3, Jacek Szaflik3, Monika Ołdak3, Kalina Burnat2
Institutions:
1Warsaw University of Technology, Warsaw, mazovian, 2Nencki Institute of Experimental Biology, PAS, Warsaw, mazovian, 3Medical University of Warsaw, Warsaw, mazovian
First Author:
Co-Author(s):
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:
Macular degeneration (MD) is the leading cause of age-related vision loss, characterized by central retinal photoreceptor degeneration, resulting in reduced high-acuity vision and difficulties with reading and object recognition.
Previously, we reported a dorsal neuroplasticity response to central retinal lesions in an MD animal model (Burnat et al., 2017), confirmed by white matter degradation (Kozak et al., 2024). Here, we examined similar reorganization in juvenile MD, the Stargardt patients, with a homogeneous genetic background.
We predicted that population receptive field (pRF) mapping (Dumoulin et al., 2008) would show increased pRF size, reflecting reduced visual acuity. Additionally, we hypothesized that retinal degeneration in Stargardt patients would induce detectable white matter changes using Fixel-Based Analysis (FBA; Raffelt et al., 2017).
Previously, we reported a dorsal neuroplasticity response to central retinal lesions in an MD animal model (Burnat et al., 2017), confirmed by white matter degradation (Kozak et al., 2024). Here, we examined similar reorganization in juvenile MD, the Stargardt patients, with a homogeneous genetic background.
We predicted that population receptive field (pRF) mapping (Dumoulin et al., 2008) would show increased pRF size, reflecting reduced visual acuity. Additionally, we hypothesized that retinal degeneration in Stargardt patients would induce detectable white matter changes using Fixel-Based Analysis (FBA; Raffelt et al., 2017).
Methods:
Participants: 22 STDG patients with no interocular differences (9m/14f, mutation in 128-kb ABCA4 gene, 19-64 years (M =37.91; SD = 12.06) and 49 healthy participants (21m/26f, 20-63 years (M = 36.34; SD = 12.45). The mapping of the population receptive field size (pRF, Dumoulin & Wandell, 2008) was performed in V1-3 visual areas, separately for their dorsal and ventral subdivisions. Two diffusion-weighted shells with b-values 1000 and 2000, 50 directions, and five b0 images (no diffusion weighting), voxel size 2x2x2 mm, TR 9200 ms, TE 95 ms, GRAPPA were acquired on 3T MR Scanner. Diffusion Weighted Imaging data processing and Fixel Based Analysis (FBA) were performed using MRTrix 3 Software (Raffelt et al., 2017, Tournier et al., 2019). Fiber Cross-section, Fiber Density and combined measure of Fiber Density and Cross-section were calculated for each subject and then statistical analysis was performed using multiple contrast matrices. Segmentation of the brain tracts was performed using TractSeg tool (Wasserthal et al., 2018). To mask main parts of tracts for analysis, for each tract, among the voxels through which the tract passes at least once, the median number of streamlines passing through each voxel was calculated. A voxel was included in the tract mask if the number of streamlines passing through it was at least equal to the median value for that tract.
·Figure 1. Explanation of the processing pipeline.
Results:
FBA and pRF analyses demonstrated hemispheric asymmetry, with greater impairment in the right hemisphere. The voxel measures in STDG showed 9-16% decrease of the FC within right posterior thalamic radiation (Figure 2), 8-60% (mean 18% STD 8.9) in FDC and 4-44% (mean 8% STD 3) in FD. The four significant streamlines were entering the right ROIs V1d and V1v, V2v, V2d, V3v and V4. In the STGD group, right hemisphere pRF size within dorsal ROIs were significantly bigger at the central eccentricities covering their blind central visual field. To ensure the changes in tracts are connected strictly with STDG, we compared left vs right hemisphere in both groups separately and no differences were found.
·Figure 2. Right hemisphere, significant streamlines colored by direction (I, III, IV) and by the effect size expressed as a percentage of FC increase (II, V).
Conclusions:
Here, we present for the first time the unilateral reduction of right white matter tracts in due to the symmetrical loss of central retina in STDG patients and demonstrate how this reduction mirrors the asymmetrical voxel activations observed within the visual cortex. The pRF sizes in the dorsal and ventral regions of interest are differentially affected by binocular loss of central vision. The increase in pRF size within central eccentricities in the dorsal stream likely reflects the central increase in visual cortex receptive field size observed in animal models of central retinal damage (Giannikopoulos & Eysel, 2006). Furthermore, the right hemispheric asymmetry in white matter microstructure has also been noted in schizophrenia patients with persistent auditory verbal hallucinations (Li et al., 2025). This unilateral right-hemisphere response is consistent with the well-established understanding of right hemisphere dominance in attention deployment (Weintraub & Mesulam, 1987).
Disorders of the Nervous System:
Neurodevelopmental/ Early Life (eg. ADHD, autism) 2
Novel Imaging Acquisition Methods:
Diffusion MRI
Perception, Attention and Motor Behavior:
Perception: Visual 1
Keywords:
Congenital
Cortex
Demyelinating
Perception
Plasticity
Tractography
Vision
Other - White matter imaging, FBA
1|2Indicates the priority used for review
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Provide references using APA citation style.
2. Dumoulin, S. O., & Wandell, B. A. (2008). Population receptive field estimates in human visual cortex. NeuroImage, 39(2), 647–660.
3. Kozak A, Ninghetto M, Wieteska M, Fiedorowicz M, Wełniak-Kamińska M, Kossowski B, Eysel UT, Arckens L, Burnat K. (2024). Visual training after central retinal loss limits structural white matter degradation: an MRI study. Behav Brain Funct.. 24;20(1):13.
4. Giannikopoulos, D. V., & Eysel, U. T. (2006). Dynamics and specificity of cortical map reorganization after retinal lesions. Proceedings of the National Academy of Sciences, 103(28), 10805–10810.
5. Li J, He J, Ren H, Li C, Li Z, Chen X, He Y, Tang J. (2025). Hemispheric asymmetry of the white matter microstructure in schizophrenia patients with persistent auditory verbal hallucinations. Cereb Cortex. 5;35(2).
6.Raffelt, D. A., Tournier, J.-D., Smith, R. E., Vaughan, D. N., Jackson, G., Ridgway, G. R., & Connelly, A. (2017). Investigating white matter fibre density and morphology using fixel-based analysis. NeuroImage, 144, 58–73.
7.Tournier, J.-D., Smith, R., Raffelt, D., Tabbara, R., Dhollander, T., Pietsch, M., Christiaens, D., Jeurissen, B., Yeh, C.-H., & Connelly, A. (2019). MRtrix3: A fast, flexible and open software framework for medical image processing and visualisation. NeuroImage, 202, 116137.
8. Wang, L., Mruczek, R. E. B., Arcaro, M. J., & Kastner, S. (2015). Probabilistic Maps of Visual Topography in Human Cortex. Cerebral Cortex, 25(10), 3911–3931.
9. Wasserthal, J., Neher, P., & Maier-Hein, K. H. (2018). TractSeg—Fast and accurate white matter tract segmentation. NeuroImage, 183, 239–253.