Jie Huang1 and David C. Zhu1,2
1Department of Radiology, Michigan State University, East Lansing, MI, United States, 2Department of Psychology, Michigan State University, East Lansing, MI
Synopsis
Areas across the visual cortex are functionally connected. A stressful striped pattern induces
perceptual illusions/distortions and visual discomfort in most people,
headaches in patients with migraine, and seizures in patients with
photosensitive epilepsy. In contrary, a non-stressful striped pattern does not
induce such effects. This study found that a 25-min visual stimulation showed a
significantly contrary effect of the stressful vs. non-stressful striped
patterns on human visual cortical functional connectivity (FC). To the contrary
of the strengthening effect of the stressful striped pattern on the FC, the
non-stressful striped pattern showed a weakening effect on the FC.
Introduction
Resting-state
(RS) functional connectivity (FC) MRI (rs-fcMRI) has been widely used to study
functional connections between brain regions, and functionally connected areas
across the visual cortex have been well recognized1,2. A stressful striped
pattern with a spatial frequency (SF) of 2.8 cycles per degree (cpd) induces
perceptual illusions/distortions and visual discomfort in most people,
headaches in patients with migraine, and seizures in patients with
photosensitive epilepsy3. In contrary, a non-stressful striped
pattern with SF 0.27 cpd does not induce such effects. Our recent study
revealed an enhancing effect of the stressful striped pattern on human visual FC4.
In this study, we further investigate the effect of the non-stressful striped pattern
on human visual FC.Methods and Materials
Twelve healthy
subjects (7 male, ages from 22 to 56) participated in this study. The
experimental conditions and tasks were identical as that in our previous study4
except that the stressful striped pattern was replaced with the non-stressful striped
pattern. Each subject had four consecutive 12-min rs-fcMRI scans under four
conditions: (1) eyes fixated on a fixation mark; (2) and (3) visual stimulation
with alternating 2-sec stimulation on-and-off for 25 min; and (4) same as (1). The
fMRI images were acquired on a GE 3T scanner with an 8-channel head coil
(TR/TE=2500/28 ms, FOV=22 cm, Matrix=64x64, slice thickness=3 mm). Same as that
in our previous study4, each subject also had a functional localizer scan that
was used to determine putative V1 seeds for generating a seed time course. In
RS analysis, after pre-processing RS time series in AFNI, the correlation
between the seed time course and the time course of every voxel in the brain
was calculated5-7. Both ROI and whole brain group analyses were
conducted. Fisher Z transformation was applied to the R values before
statistical analyses. For ROI analysis in native space, for each of the four RS
conditions, two FC maps were computed at two levels of significance: (1)
P=1.0x10-5 and (6) P=1.0x10-10. For each significance
level, the four FC maps were first used to determine a joint ROI mask in the
visual cortex across all the four RS conditions, and then the mask was used to obtain
a ROI-mean R value for each RS condition. Then, for each of the two P values,
the group-mean of the ROI-mean R values of the 12 subjects was computed and
analyzed to investigate the non-stressful visual stimulation effect on the FC.
To reduce inter-subject and inter-study variations, each ROI-mean R value of
the four RS conditions was normalized by dividing it with the baseline ROI-mean
R value for each subject, enabling a comparison of this study with our previous
study4. In whole-brain group analyses, the correlation maps of all
subjects were warped to the ICBM 452 template. Whole-brain ANOVAs were carried
to compare the Z values between different RS conditions.Results and Discussion
The contrary effect
of the stressful vs. non-stressful striped patterns on the visual cortical FC
is illustrated in Fig. 1. The size of the ROI mask in the visual cortex varied
with the significance level, similar as that in our previous study4.
The ROI analysis showed that the stimulation significantly increased the R
value in comparison to the baseline R value during the first half of the 25-min
stimulation (paired t-test, max P=0.0017) (Fig. 2), similarly as that in our
previous study4. In contrary to the continued enhancement in the
previous study, the R value was reduced back to the baseline R value during the
second half of the 25-min stimulation, showing a significantly contrary effect
between the stressful and non-stressful striped patterns (P=0.0091). After the
cessation of the stimulation, the visual cortical FC showed a larger but not
significant R value than that in the baseline (paired t-test, P=0.34). Besides
within the visual cortex, our previous study4 found significantly
enhanced connections between V1 and the other brain regions under the stressful
stimulation (Fig. 3). In contrary, the whole-brain ANOVAs of this study did not
find significant FC changes between pre-VS and post-VS under the non-stressful
stimulation.Conclusion
The 25-min visual stimulation showed a
significantly contrary effect of the stressful vs. non-stressful striped
patterns on the FC within the visual cortex. There was a lasting effect even after the
cessation of the stimulation under the stressful stimulation, both within and
beyond the visual region, but not under the non-stressful stimulation. This
suggests prolonged visual stimulation with stressful striped patterns may alter
visual system FC network and its relationship with other networks.Acknowledgements
No acknowledgement found.References
1. Biswal B, et al. Functional connectivity in the motor cortex of resting
human brain using echo-planar MRI. Magn Reson Med 34:537-541, 1995.
2. Yeo TBT, et al. The organization of the human cerebral cortex estimated by
intrinsic functional connectivity. J Neurophysiol 106:1125-1165, 2011.
3. Wilkins AJ. Visual Stress. Oxford: Oxford University Press, 1995.
4. Huang J and Zhu D. Visual Stimulation Altered Human Visual Cortical
Functional Connectivity. Proc. Intl. Soc. Mag. Reson. Med. 24, 1671, 2016.
5. Cox RW. AFNI: software for analysis and visualization of functional
magnetic resonance neuroimages. Comput Biomed Res 29:162-173, 1996.
6. Fox MD, et al. The human brain is intrinsically organized into dynamic,
anticorrelated functional networks. Proc Natl Acad Sci USA 102:9673-9678, 2005.
7. Zhu DC and Majumdar S. Integration of Resting-State FMRI and
Diffusion-Weighted MRI Connectivity Analyses of the Human Brain: Limitations
and Improvement. J Neuroimaging 24:176-186, 2014.