Mapping Layer-specific Orientation Pinwheel Pattern in Cat Visual Cortex with Functional CBV Imaging

Poster No:

2387 

Submission Type:

Abstract Submission 

Authors:

Shinho Cho1, Djaudat Idiyatullin1, Wei Zhu1, Xiao-Hong Zhu1, Kamil Uğurbil1, Wei Chen1

Institutions:

1Center for Magnetic Resonance Research and Department of Radiology, University of Minnesota, Minneapolis, MN

First Author:

Shinho Cho  
Center for Magnetic Resonance Research and Department of Radiology, University of Minnesota
Minneapolis, MN

Co-Author(s):

Djaudat Idiyatullin  
Center for Magnetic Resonance Research and Department of Radiology, University of Minnesota
Minneapolis, MN
Wei Zhu  
Center for Magnetic Resonance Research and Department of Radiology, University of Minnesota
Minneapolis, MN
Xiao-Hong Zhu  
Center for Magnetic Resonance Research and Department of Radiology, University of Minnesota
Minneapolis, MN
Kamil Uğurbil  
Center for Magnetic Resonance Research and Department of Radiology, University of Minnesota
Minneapolis, MN
Wei Chen  
Center for Magnetic Resonance Research and Department of Radiology, University of Minnesota
Minneapolis, MN

Introduction:

Optical imaging and single-unit recording in the mammalian visual cortex have reported the map of orientation preference domains in the superficial layer (Ohki et al., 2000; O'Herron et al., 2016) and orientation tuning property (Ringach et al., 2005), but with limited cortical depth or field-of-view (FOV) that profiles functional map across layers. We examined layer-specific cerebral blood volume (CBV) responses to orientation stimuli in the cat visual cortex (n = 4) and demonstrated the characteristic 'pinwheel' pattern map of orientation preference in different cortical layers by using an ultra-high field fMRI (9.4 Tesla) with unprecedentedly high echo-planar imaging resolution (250 μm isotropic voxel).

Methods:

Four cats (0.8–1.6 kg), anesthetized with 0.8-1.0% isoflurane and intravenously administered with an exogenous contrast agent for CBV-based fMRI (Feraheme® 0.75 cc/kg) were used upon the protocol approved by the University of Minnesota Institutional Animal Care and Use Committee. For visual stimulation, bi-directional drifting, square-wave gratings were presented (spatial frequency = 0.15 cycle/°; temporal frequency 2 cycle/s, drifting direction reversed every 5 s; eight orientations, 0°, 22.5°, 45.0°, 67.5°, 90°, 112.5°, 135°, and 157.5° were randomly ordered) for 10 secs and the inter-stimulus interval was 20 secs. Each scan was repeated up to 20 times per a subject on a 9.4-Tesla MRI system (Agilent, Santa Clara, CA) with a 15-mm diameter single-loop radio frequency (RF) coil: anatomical imaging (Gradient echo, data matrix = 256×256, FOV = 32×32 mm, in-plane resolution = 125×125 μm, slice thickness 250 μm, TR = 300 ms, and TE = 10 ms) and GE-EPI fMRI (6 axial, 250 μm thickness slices, data matrix = 128×128, FOV = 32 × 32 mm, in-plane resolution = 250×250 μm, TR = 2 secs, TE = 10 ms). For data analysis, conventional preprocessing (slice-timing & motion correction, spatial smoothing with 250 μm, and bandpass filtering with 0.01 – 0.3 Hz) was carried out with the Analysis of Functional Neuroimages (AFNI) (Cox, 1996). General linear modeling and the orientation tuning curve fitting (Villeneuve et al., 2009) were followed.

Results:

Orientation gratings induced significant cerebral blood volume response across the visual cortex (500 μm cortical depth in Area 18, -1.0 to -6.0% signal change) (Fig. 1A). The outcome of orientation tuning curve fitting showed the characteristic spatial pattern of the iso-orientation domain (Fig. 1B); the Poincaré-Hopf index calculation and Voronoi tessellation revealed the location of pinwheel centers and the extent of the pinwheel ('Hyper-column') (Fig 1C. and Fig. 1D). The spatial pattern varied upon the cortical depth; the across-cortex spacing of pinwheel centers was 0.83±0.5 mm across all layers (Fig. 2A), but notably, the spacing gets linearly larger as cortical depth growing (r = 0.9, R-square = 0.87, p < 0.05) as well as the extent of pinwheel domain gets broader as cortical depth growing (Fig. 2B), which shows the similar linear trend with the pinwheel spacing (r = 0.64~0.89, p < 0.5).
Supporting Image: fig1.png
Supporting Image: fig2.png
 

Conclusions:

Ultra-high field MRI with high resolution of echo-planar imaging (250 μm isotropic voxel) enabled us to characterize the depth-specific orientation preference map based on CBV responses as showing sparser pinwheel arrangement in deep cortical area. The present high-resolution fMRI approach can lay the groundwork for future studies to resolve whether layer-dependent hemodynamic signal corresponds to neuronal selectivity in the meso-scale neural circuits.

This work was supported by NIH grants: R01 MH111447, R01 MH111413, R01 NS118330, P41 EB027061 and P30 NS076408; and WM KECK foundation.

Novel Imaging Acquisition Methods:

BOLD fMRI 1

Perception, Attention and Motor Behavior:

Perception: Visual 2

Keywords:

ANIMAL STUDIES
Cortical Layers
FUNCTIONAL MRI
HIGH FIELD MR
Perception
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):

Healthy subjects

Are you Internal Review Board (IRB) certified? Please note: Failure to have IRB, if applicable will lead to automatic rejection of abstract.

No

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.

Not applicable

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?

If Other, please list  -   9.4T

Which processing packages did you use for your study?

AFNI

Provide references using author date format

Cox RW. AFNI: software for analysis and visualization of functional magnetic resonance neuroimages. Computers and Biomedical research. 1996;29(3):162-173. doi: 10.1006/cbmr.1996.0014
Ohki K, Matsuda Y, Ajima A, Kim D-S, Tanaka S. Arrangement of orientation pinwheel centers around area 17/18 transition zone in cat visual cortex. Cerebral Cortex. 2000;10(6):593-601. doi: 10.1093/cercor/10.6.593
O’Herron P, Chhatbar PY, Levy M, et al. Neural correlates of single-vessel haemodynamic responses in vivo. Nature. 2016;534(7607):378-382. doi: 10.1038/nature17965
Ringach DL, Shapley RM, Hawken MJ. Orientation selectivity in macaque V1: diversity and laminar dependence. The Journal of neuroscience : the official journal of the Society for Neuroscience. Jul 1 2002;22(13):5639-51. doi: 10.1523/JNEUROSCI.22-13-05639.2002
Villeneuve M, Vanni M, Casanova C. Modular organization in area 21a of the cat revealed by optical imaging: comparison with the primary visual cortex. Neuroscience. 2009;164(3):1320-1333. doi: 10.1016/j.neuroscience.2009.08.042