Layer-dependent amblyopic deficits in feedforward and lateral processing in human early visual corte

Poster No:

2632 

Submission Type:

Abstract Submission 

Authors:

Yue Wang1,2, Chencan Qian1,2, Wen Wen3, Peng Zhang1,2

Institutions:

1UCAS, University of Chinese Academy of Sciences, 100049 Beijing, China, 2IBP, State Key Laboratory of Brain and Cognitive Science, Institute of Biophysics,, 3Fudan University, Department of Ophthalmology & Visual Science, Eye & ENT Hospital, Shanghai Medical College

First Author:

Yue Wang  
UCAS|IBP
University of Chinese Academy of Sciences, 100049 Beijing, China|State Key Laboratory of Brain and Cognitive Science, Institute of Biophysics,

Co-Author(s):

Chencan Qian  
UCAS|IBP
University of Chinese Academy of Sciences, 100049 Beijing, China|State Key Laboratory of Brain and Cognitive Science, Institute of Biophysics,
Wen Wen  
Fudan University
Department of Ophthalmology & Visual Science, Eye & ENT Hospital, Shanghai Medical College
Peng Zhang  
UCAS|IBP
University of Chinese Academy of Sciences, 100049 Beijing, China|State Key Laboratory of Brain and Cognitive Science, Institute of Biophysics,

Introduction:

Amblyopia or lazy eye is the most common cause of uniocular vision loss in adults, caused by disruptions to early visual development. The precise neural deficits of amblyopia in the human brain remain unclear. Using layer-dependent 7T fMRI, we investigated functional deficits to feedforward, lateral and feedback processing in the early visual cortex of adult human amblyopia.

Methods:

10 unilateral amblyopia patients with anisometropia participated (25±10, 3 male). Full contrast checkerboard patterns counter-phase flickering at 4Hz (35 degrees of visual angle in width and height) were presented to the amblyopic eye, to the fellow eye, or to both eyes of patients with MRI compatible goggle displays (NNL). Each subject completed 9 fMRI runs, each run lasted 288 seconds. Stimuli were presented for 18 seconds, in alteration with 12 seconds fixation. Subjects were instructed to maintain fixation during the experiment. MRI data were acquired on a 7T MRI scanner (Siemens Magnetom) with a 32-channel receive 4-channel transmit visual coil. Gradient coil has a maximum amplitude of 70mT/m, 200us minimum gradient rise time, and 200T/m/s maximum slew rate. Functional data were collected with a T2*-weighted 2D GE-EPI sequence (26 axial slices, TR = 2000 ms, TE = 22 ms, image matrix =150×150, FOV = 180×180 mm, GRAPPA acceleration factor = 2, Flip angle=80°, partial Fourier = 6/8, phase encoding direction from A to P). Before each functional scan, five EPI images with reversed phase encoding direction (P to A) were also acquired for EPI distortion correction. Anatomical volumes were acquired with a T1-MP2RAGE sequences at 0.7 mm isotropic resolution (256 sagittal slices, centric phase encoding, acquisition matrix=320×320, Field of view = 224×224 mm, GRAPPA=3, TR = 4000 ms, TE=3.05 ms, TI1 = 750ms, flip angle = 4°, TI2 = 2500 ms, flip angle = 5°). Subjects used bite bars to restrict head motion.

Results:

Figure 1 shows the fMRI response and amblyopic deficit index (1 – AE/FE) in monocular and binocular conditions. In monocular conditions, amblyopic deficits were comparable across different cortical depth of V1, consistent with deficits in feedforward processing from the thalamic input. The monocular deficit index was also comparable across the early visual areas from V1 to V4. In the binocular condition, the amblyopic deficit index was strongest in the superficial depth of V1, suggesting additional deficits in lateral processing in the superficial layers.
Figure 2 shows the layer-dependent effective connectivity results with dynamic causal modeling (DCM) analysis. Monocular stimulus presented to the amblyopic eye shows significantly reduced feedforward connectivity from the superficial layers of V1 to the middle layers of V2. During binocular presentation, in addition to amblyopic deficits in feedforward connectivity, V1 superficial layers show mutual inhibition between the two eyes. It supports additional amblyopic deficits during lateral processing in the superficial layers.
Supporting Image: figure1.jpg
Supporting Image: figure2.jpg
 

Conclusions:

Layer-dependent response and connectivity analysis show reduced feedforward processing for monocular stimulus presented to the amblyopic eye, supporting a thalamic origin of amblyopic deficits. During binocular presentation, in addition to functional loss on feedforward processing, the amblyopic eye showed strongest response loss in the superficial depth of V1 due to lateral interactions. These findings reveal the precise neural deficits of amblyopic on visual cortical circuits, which may shed lights for developing new tools for treating amblyopia and tracking the prognosis.

Modeling and Analysis Methods:

Connectivity (eg. functional, effective, structural) 2

Novel Imaging Acquisition Methods:

BOLD fMRI 1

Perception, Attention and Motor Behavior:

Attention: Visual

Keywords:

Cortical Layers
FUNCTIONAL MRI
Vision

1|2Indicates the priority used for review

My abstract is being submitted as a Software Demonstration.

No

Please indicate below if your study was a "resting state" or "task-activation” study.

Task-activation

Healthy subjects only or patients (note that patient studies may also involve healthy subjects):

Patients

Was any human subjects research approved by the relevant Institutional Review Board or ethics panel? NOTE: Any human subjects studies without IRB approval will be automatically rejected.

Yes

Was any animal research approved by the relevant IACUC or other animal research panel? NOTE: Any animal studies without IACUC approval will be automatically rejected.

Yes

Please indicate which methods were used in your research:

Functional MRI

For human MRI, what field strength scanner do you use?

7T

Which processing packages did you use for your study?

AFNI
SPM

Provide references using author date format

Hess, R. F., X. F. Li, B. Mansouri, B. Thompson and B. C. Hansen (2009). "Selectivity as well as Sensitivity Loss Characterizes the Cortical Spatial Frequency Deficit in Amblyopia." Human Brain Mapping 30(12): 4054-4069.
Liu, C., Guo, F., Qian, C., Zhang, Z., Sun, K., Wang, D. J., ... & Zhang, P. (2020). Layer-dependent multiplicative effects of spatial attention on contrast responses in human early visual cortex. Progress in Neurobiology, 101897.
Zeidman, P., Jafarian, A., Corbin, N., Seghier, M. L., Razi, A., Price, C. J., & Friston, K. J. (2019). A guide to group effective connectivity analysis, part 1: First level analysis with DCM for fMRI. NeuroImage, 200, 174-190.
Zeidman, P., Jafarian, A., Seghier, M. L., Litvak, V., Cagnan, H., Price, C. J., & Friston, K. J. (2019). A guide to group effective connectivity analysis, part 2: Second level analysis with PEB. NeuroImage, 200, 12-25.
Zarghami, T. S., & Friston, K. J. (2020). Dynamic effective connectivity. Neuroimage, 207, 116453.