Ting-Chih Wang1, Yao-Chia Shih2,3, Hong-Huei Liu4, and Wen-Yih Issac Tseng3,5
1Department of Electrical Engineering, National Taiwan University, Taipei, Taiwan, 2Institute of Biomedical Engineering, National Taiwan University, Taipei, Taiwan, 3Institute of Medical Device and Imaging, National Taiwan University College of Medicine, Taipei, Taiwan, 4Department of Neurology, National Taiwan University Hospital, College of Medicine, National Taiwan University, Taipei, Taiwan, 5Molecular Imaging Center, National Taiwan University, Taipei, Taiwan
Synopsis
Kleine-Levin
Syndrome is a rare neurological disorder characterized
by recurrent episodes of excessive sleepiness and other symptoms listed in the
ICSD Diagnostic Criteria for KLS. Its etiology is still unknown nowadays. The
most consistent finding in KLS is abnormal thalamic function. Here, we used
seed-based analysis to analyze resting state fMRI obtained from 2 patients with
KLS. In bilateral thalamic seeding, both patients showed decreased connection
between the thalamus and the anterior cingulate cortex. This result could be
attributed to alteration of the dorsal pathway in ascending arousal system, and
might also explain their attention deficits.Purpose
Kleine-Levin Syndrome (KLS) is a rare neurological disorder
characterized by recurrent episodes of excessive sleepiness and other symptoms
listed in the ICSD Diagnostic Criteria for KLS. To date, the etiology of KLS is
still unknown. The most consistent finding in KLS is abnormal thalamic
function. Thalamic abnormality was reported from task fMRI of working memory as
well as from SPECT studies. During
working memory tasks, KLS patients consistently show hyperactivation in the
left thalamus as compared to healthy controls. They also show less
activation in the anterior cingulate cortex
1 (ACC). Besides, one research suggests that thalamus may represent the
functional interface between the arousal and the attentional systems
2.
Another research further relates such attention to ACC
3.
Therefore, the purpose of this study is to examine functional connectivity of
the thalamus in resting state fMRI. Specifically, we are interested in functional
connectivity between the thalamus and ACC.
Methods
One male patient and one
female patient with KLS were recruited in the study. They were brother (28
years old, disease duration = 11 years) and sister (30 years old, disease
duration = 13 years). Aside from hypersomnia, the male patient’s attention and
reading ability were also compromised. The female patient was found to have
decreased cognitive ability, working memory and attention. Both patients received MRI scans in aggravated
and sober conditions. The aggravated condition was considered when patients’
sleep exceeded 15 hours per day. The sober condition was considered when
patients resumed normal sleep duration. For comparison, ten healthy people (mean
age = 25.2 ± 7.2 years) were also recruited to the study. All
participants received MRI scans on a 3 Tesla MRI system (Tim Trio, Siemens,
Erlangen, Germany) with a 32-channel phased array head coil. T1-weighted
imaging was performed using a 3D MPRAGE sequence: TR / TE = 2000 ms / 3 ms,
flip angle = 9°, FOV = 256 × 192 × 208 mm^3, acquisition matrix = 256 × 192 ×
208. Multi-echo resting state fMRI was performed using a 2D gradient echo EPI sequence
4:
TR / TE = 2550 ms / 12, 28, 44, 60 ms, flip angle = 90°, FOV = 240 × 240 mm^2, slice
thickness = 2.5 mm, and acquisition matrix = 64 × 64. The anatomical image was
first skull-stripped and then warped nonlinearly to MNI anatomical template
using FSL FNIRT. Denoising was applied after optimal combination of echoes and
regressing out motion and high-frequency signals using AFNI tool 3dbandpass.
Regression models for motion artifact included rigid body parameters for the
alignment of all fMRI volumes to a reference volume. Before regression, data
were despiked with a tanh function. After preprocessing, the data were
decomposed with FastICA to remove non- BOLD components. Then, we extracted time
courses to obtain seed region, nuisance regressors using spm8. The bilateral thalamus seeding ROI was generated using WFU_PickAtlas
5-7.
All these regressors were organized into a design matrix of a general linear
model
8,9. Using this design matrix, we computed a contrast image that
represented signals coherent with seed region signal.
Results
Figure
1a shows the contrast of bilateral thalamic seeding in the male patient. The
activation of ACC is decreased as compared to normal controls.
In addition, the activation in bilateral insula (t-value = 3.78) is increased. These results indicate that the
connection between the thalamus and ACC and the connection between the thalamus and insula have been altered in opposite
directions. Figure 1b shows the contrast of bilateral thalamic seeding in the
female patient. The activation of ACC is decreased as compared to normal controls. The result indicates that
the connection between the thalamus and ACC is probably compromised. Figure 2 shows the contrast of bilateral
thalamic seeding between normal control and the two patients in sagittal view.
Both patients show less activation in ACC compared to normal control.
Discussion
In our patients with KLS, we found that their
connections between the thalamus and ACC were
decreased compared to normal controls. This
malfunctioning connection might explain their symptoms of hypersomnia. Incidentally,
we found hyperactivation in the thalamic-insular connection in the male patient.
It has been reported that insula plays a role between sleep and conscious
10.
However, we found insular hyperactivation only in male patient, but no obvious
activation in female patient. This might result from the heterogeneity of the
disease.
Conclusion
The future work will
involve investigation of the mechanism of the decreased connection between ACC and thalamus. The
unique increase in the connection between the thalamus and insula in our male
patient also warrants further investigation.
Acknowledgements
No acknowledgement found.References
1. Engström, Vigren, Karlsson, et
al. Working memory in 8 Kleine-Levin syndrome patients: An fMRI study. Sleep. 2009;32(5):681-8.
2. Portas, Rees,
Howseman, et al. A Specific Role for the
Thalamus in Mediating the Interaction of Attention and Arousal in Humans. J Neurosci. 1998;18(21):8979-89.
3. Weissman, Gopalakrishnan, Hazlett, et al. Dorsal
Anterior Cingulate Cortex Resolves Conflict from Distracting Stimuli by
Boosting Attention toward Relevant Events. Cereb Cortex. 2005;15(2):229-37.
4. Evans,
Kundu, Horovitz, et al. Separating slow BOLD from non-BOLD baseline drifts
using multi-echo fMRI. Neuroimage. 2015;105:189-97.
5. Lancaster,
Rainey, Summerlin, et al. Automated labeling of the human brain: a preliminary
report on the development and evaluation of a forward-transform method. Hum Brain Mapp. 1997;5(4):238-42.
6. Lancaster,
Woldorff, Parsons, et al. Automated Talairach atlas labels for functional brain
mapping. Hum Brain Mapp. 2000;10(3):120-31.
7. Maldjian, Laurienti,
Kraft, et al. An automated method for
neuroanatomic and cytoarchitectonic atlas-based interrogation of fMRI data
sets. Neuroimage. 2003 ;19(3):1233-9.
8. Friston, Frith, Frackowiak, et al. Characterizing
dynamic brain responses with fMRI: a multivariate approach. Neuroimage. 1995;2(2):166-72.
9. Fox, Snyder, Vincent, et al. The human brain is
intrinsically organized into dynamic, anticorrelated functional networks. Proc Natl Acad Sci U S A. 2005;102(27):9673-8.
10. Czisch,
Wehrle, Harsay, et al. On
the Need of Objective Vigilance Monitoring: Effects of Sleep Loss on Target
Detection and Task-Negative Activity Using Combined EEG/fMRI. Front Neurol. 2012; 3: 67.