Microglia Density and Its Association With Disease Duration, Severity, and Orexin Levels in Patients With Narcolepsy Type 1.

BACKGROUND AND OBJECTIVES: Narcolepsy type 1 (NT1) is due to the loss of hypothalamic neurons that produce orexin (ORX), by a suspected immune-mediated process. Rare postmortem studies are available and failed to detect any inflammation in the hypothalamic region, but these brains were collected years after the first symptoms. In vivo studies close to disease onset are lacking. We aimed to explore microglia density in the hypothalamus and thalamus in NT1 compared with controls using [18F]DPA-714 PET and to study in NT1 the relationships between microglia density in the hypothalamus and in other regions of interest (ROIs) with disease duration, severity, and ORX levels. METHODS: Patients with NT1 and controls underwent a standardized clinical evaluation and [18F]DPA-714 PET imaging using a radiolabeled ligand specific to the 18 kDa translocator protein (TSPO). TSPO genotyping determined receptor affinity. Images were processed on peripheral module interface using standard uptake value (SUV) on ROIs: hypothalamus, thalamus, frontal area, cerebellum, and the whole brain. SUV ratios (SUVr) were calculated by normalizing SUV with cerebellum uptake. RESULTS: A total of 41 patients with NT1 (21 adults, 20 children, 10 with recent disease onset <1 year) and 35 controls were included, with no significant difference between groups for [18F]DPA-714 binding (SUV/SUVr) in the hypothalamus and thalamus. Unexpectedly, significantly lower SUVr in the whole brain was found in NT1 compared with controls (0.97 ± 0.06 vs 1.08 ± 0.22, p = 0.04). The same finding between NT1 and controls in the whole brain was observed in those with high or mixed TSPO affinity (p = 0.03 and p = 0.04). Similar trend was observed in the frontal area in NT1 (0.96 ± 0.09 vs 1.09 ± 0.25, p = 0.05). In NT1, no association was found between SUVr in different ROIs and age, disease duration, severity, or ORX levels. DISCUSSION: We found no evidence of in vivo increased microglia density in NT1 compared with controls, even close to disease onset, and even unexpectedly a decrease in the whole brain of these patients. These findings do not support the presence of neuroinflammation in the destruction process of ORX neurons. TRIAL REGISTRATION INFORMATION: ClinicalTrials.org NCT03754348.

Microstructural White Matter Abnormalities in Children and Adolescents With Narcolepsy Type 1.

BACKGROUND: In 2010, the H1N1 Pandemrix vaccination campaign was followed by a sudden increase in narcolepsy type 1 (NT1). We investigated the brain white matter microstructure in children with onset of NT1 within two years after the Pandemrix vaccination. METHODS: We performed diffusion-weighted magnetic resonance imaging (MRI) on 19 children and adolescents with NT1 and 19 healthy controls. Imaging was performed at a median of 4 years after the diagnosis at a median age of 16 years. For the MRI, we used whole-brain tractography and tract-based spatial statistics (TBSS). We compared these results with medical records and questionnaire data. RESULTS: Narcoleptic children showed a global decrease in mean, axial, and radial diffusivity and an increase in planarity coefficient in the white matter TBSS skeleton and tractography. These differences were widespread, and there was an increased asymmetry of the mean diffusivity in children with NT1. The global microstructural metrics were reflected in behavior, and especially the axial diffusion levels correlated with anxiety and depression symptoms and social and behavioral problems. CONCLUSIONS: In pediatric patients with Pandemrix-associated NT1, several global changes in the brain white matter network skeleton were observed within five years after the onset of NT1. The degree of changes correlates with behavioral problems.

Disrupted topological properties of structural brain networks present a glutamatergic neuropathophysiology in people with narcolepsy.

STUDY OBJECTIVES: Growing evidences have documented various abnormalities of the white matter bundles in people with narcolepsy. We sought to evaluate topological properties of brain structural networks, and their association with symptoms and neuropathophysiological features in people with narcolepsy. METHODS: Diffusion tensor imaging was conducted for people with narcolepsy (n = 30) and matched healthy controls as well as symptoms assessment. Structural connectivity for each participant was generated to analyze global and regional topological properties and their correlations with narcoleptic features. Further human brain transcriptome was extracted and spatially registered for connectivity vulnerability. Genetic functional enrichment analysis was performed and further clarified using in vivo emission computed tomography data. RESULTS: A wide and dramatic decrease in structural connectivities was observed in people with narcolepsy, with descending network degree and global efficiency. These metrics were not only correlated with sleep latency and awakening features, but also reflected alterations of sleep macrostructure in people with narcolepsy. Network-based statistics identified a small hyperenhanced subnetwork of cingulate gyrus that was closely related to rapid eye movement sleep behavior disorder (RBD) in narcolepsy. Further imaging genetics analysis suggested glutamatergic signatures were responsible for the preferential vulnerability of connectivity alterations in people with narcolepsy, while additional PET/SPECT data verified that structural alteration was significantly correlated with metabotropic glutamate receptor 5 (mGlutR5) and N-methyl-D-aspartate receptor (NMDA). CONCLUSIONS: People with narcolepsy endured a remarkable decrease in the structural architecture, which was not only closely related to narcolepsy symptoms but also glutamatergic signatures.

The application of machine learning on brain imaging features of different narcolepsy subtypes.

STUDY OBJECTIVES: Narcolepsy is a central hypersomnia disorder, and differential diagnoses between its subtypes can be difficult. Hence, we applied machine learning to analyze the positron emission tomography (PET) data of patients with type 1 or type 2 narcolepsy, and patients with type 1 narcolepsy and comorbid schizophrenia, to construct predictive models to facilitate the diagnosis. METHODS: This is a retrospective and prospective case-control study of adolescent and young adult patients with type 1 or type 2 narcolepsy, and type 1 narcolepsy and comorbid schizophrenia. All participants received 18-F-fluorodeoxy glucose PET, sleep studies, neurocognitive tests, sleep questionnaires, and human leukocyte antigen typing. The collected PET data were analyzed by feature selections and classification methods in machine learning to construct predictive models. RESULTS: A total of 314 participants with narcolepsy were enrolled; 204 had type 1 narcolepsy, 90 had type 2 narcolepsy, and 20 had type 1 narcolepsy and comorbid schizophrenia. We used three filter methods for feature selection followed by a comparative analysis of classification methods. To apply a small number of regions of interest (ROI) and high classification accuracy, the Naïve Bayes classifier with the Term Variance as feature selection achieved the goal with only three ROIs (left basal ganglia, left Heschl, and left striatum) and produced an accuracy of higher than 99%. CONCLUSIONS: The accuracy of our predictive model of PET data are promising and can aid clinicians in the diagnosis of narcolepsy subtypes. Future research with a larger sample size could further refine the predictive model of narcolepsy.

Resting-State Functional Magnetic Resonance Imaging as an Indicator of Neuropsychological Changes in Type 1 Narcolepsy.

RATIONALE AND OBJECTIVES: To explore indicators of neuropsychological changes in patients with type 1 narcolepsy (NT1) using resting-state functional magnetic resonance imaging (rs-fMRI). MATERIALS AND METHODS: Thirty-four NT1 patients and 34 age- and sex-matched healthy volunteers were recruited for neuropsychiatric assessments and rs-fMRI data acquisition. Fractional amplitude of low-frequency fluctuations (fALFF), regional homogeneity (ReHo), and related brain functional connectivity (FC) were calculated for the two groups and compared using a two-sample t test with cluster-level FDR correction. Moreover, partial correlation analysis was performed between these functional values of changed brain regions and clinical scales. RESULTS: Compared to those of healthy controls, spontaneous functional activities were significantly weakened in patients with NT1 in regions such as the left/right posterior cerebellum lobe, left inferior temporal gyrus, and left dorsolateral superior frontal gyrus, whereas those in regions such as the left middle occipital gyrus, right inferior occipital gyrus, and left/right lingual gyrus were significantly strengthened. Furthermore, NT1 patients displayed significantly changed FCs between the left/right anterior cingulate gyrus (ACG) and regions such as the left/right cerebellum, left middle occipital gyrus, and left inferior frontal gyrus in the operculum. In partial correlation analysis, the functions in the left dorsolateral superior frontal gyrus were significantly related to the Trail Making Tests (TMT) score. Moreover, the FC between the left ACG and left inferior frontal gyrus in the operculum was highly correlated with anxiety and depression features, including the Hamilton Anxiety Scale (HAMA) score and Hamilton Depression Rating Scale (HAMD-17) score. CONCLUSION: Patients with NT1 exhibited abnormalities in the anterior cingulate cortex, frontal-parietal cortex, hippocampus, and left/right posterior cerebellum lobe. The deactivation of the left frontal-temporal cortex is stronger, which is involved in the cognitive decline and mental disorders in these patients. Damage to the ACG may affect its FC with other regions and cause cognition and emotion dysregulation, perhaps by impairing patients' visual pathways and frontal-temporal-parietal networks. Hence, these could be important biomarkers for their neuropsychological changes.

18F-FDG Brain PET Findings in Narcolepsy Type 2.

ABSTRACT: A 16-year-old adolescent boy with extensive travel throughout West Africa presented with a 6-year history of social withdrawal, anhedonia, and daytime sleepiness. The patient's electroencephalography was normal. Initial MRI revealed small pituitary gland and left temporal developmental venous anomaly. Subsequently obtained 18F-FDG brain PET was notable for markedly severe hypometabolism in the brainstem. Further workup revealed a normal orexin, autoimmune encephalitis panel, and negative titers for Trypanosoma brucei and cruzi in the CSF. Outpatient sleep study showed mild obstructive sleep apnea, and multiple sleep latency test revealed reduced mean sleep latency at 7 minutes with sleep-onset REM in 3/5 naps, findings consistent with narcolepsy type 2.

Alterations in the structural covariance network of the hypothalamus in patients with narcolepsy.

PURPOSE: The hypothalamus plays a pivotal role in the pathogenesis of narcolepsy. This study aimed to evaluate the differences in the structural covariance network of thehypothalamus based on volume differences between patients with narcolepsy and healthy controls. METHODS: We retrospectively enrolled 15 patients with narcolepsy and 19 healthy controls.All subjects underwent three-dimensional T1-weighted imaging using a 3-T magnetic resonance imaging scanner. Hypothalamic subunits were segmented, and the volumes of individual hypothalamic subunits were obtained using the FreeSurfer program. Subsequently, we conducted a structural covariance network analysis of the subunit volumes with graph theory using the BRAPH program in patients with narcolepsy and in healthy controls. RESULTS: There were no significant differences in the volumes of the entire right and left hypothalamus nor in the hypothalamic subunit between patients with narcolepsy and healthy controls. However, we found significant differences in the structural covariance network in the hypothalamus between these groups. The characteristic path length was significantly lower in patients with narcolepsy than in healthy controls (1.698 vs. 2.831, p = 0.001). However, other network measures did not differ between patients with narcolepsy and healthy controls. CONCLUSION: We found that the structural covariance network of the hypothalamus, as assessed from the subunit volumes of hypothalamic regions using a graph theoretical analysis, is different in patients with narcolepsy compared to healthy controls. These findings may contribute to the understanding of the pathogenesis of narcolepsy.

Reduced Numbers of Corticotropin-Releasing Hormone Neurons in Narcolepsy Type 1.

Narcolepsy type 1 (NT1) is a chronic sleep disorder correlated with loss of hypocretin(orexin). In NT1 post-mortem brains, we observed 88% reduction in corticotropin-releasing hormone (CRH)-positive neurons in the paraventricular nucleus (PVN) and significantly less CRH-positive fibers in the median eminence, whereas CRH-neurons in the locus coeruleus and thalamus, and other PVN neuronal populations were spared: that is, vasopressin, oxytocin, tyrosine hydroxylase, and thyrotropin releasing hormone-expressing neurons. Other hypothalamic cell groups, that is, the suprachiasmatic, ventrolateral preoptic, infundibular, and supraoptic nuclei and nucleus basalis of Meynert, were unaffected. The surprising selective decrease in CRH-neurons provide novel targets for diagnostics and therapeutic interventions. ANN NEUROL 2022;91:282-288.

Hypothalamus and amygdala functional connectivity at rest in narcolepsy type 1.

INTRODUCTION: functional and structural MRI studies suggest that the orexin (hypocretin) deficiency in the dorso-lateral hypothalamus of narcoleptic patients would influence both brain metabolism and perfusion and would cause reduction in cortical grey matter. Previous fMRI studies have mainly focused on cerebral functioning during emotional processing. The aim of the present study was to explore the hemodynamic behaviour of spontaneous BOLD fluctuation at rest in patients with Narcolepsy type 1 (NT1) close to disease onset. METHODS: Fifteen drug naïve children/adolescents with NT1 (9 males; mean age 11.7 ± 3 years) and fifteen healthy children/adolescents (9 males; mean age 12.4 ± 2.8 years) participated in an EEG-fMRI study in order to investigate the resting-state functional connectivity of hypothalamus and amygdala. Functional images were acquired on a 3 T system. Seed-based functional connectivity analyses were performed using SPM12. Regions of Interest were the lateral hypothalamus and the amygdala. RESULTS: compared to controls, NT1 patients showed decreased functional connectivity between the lateral hypothalamus and the left superior parietal lobule, the hippocampus and the parahippocampal gyrus. Decreased functional connectivity was detected between the amygdala and the post-central gyrus and several occipital regions, whereas it was increased between the amygdala and the inferior frontal gyrus, claustrum, insula, and putamen. CONCLUSION: in NT1 patients the abnormal connectivity between the hypothalamus and brain regions involved in memory consolidation during sleep, such as the hippocampus, may be linked to the loss of orexin containing neurons in the dorsolateral hypothalamus. Moreover, also functional connectivity of the amygdala seems to be influenced by the loss of orexin-containing neurons. Therefore, we can hypothesize that dysfunctional interactions between regions subserving the maintenance of arousal, memory and emotional processing may contribute to the main symptom of narcolepsy.

Morphological and Age-Related Changes in the Narcolepsy Brain.

Morphological changes in the cortex of narcolepsy patients were investigated by surface-based morphometry analysis in this study. Fifty-one type 1 narcolepsy patients and 60 demographically group-matched healthy controls provided resting-state functional and high-resolution 3T anatomical magnetic resonance imaging scans. Vertex-level cortical thickness (CT), gyrification, and voxel-wise functional connectivity were calculated. Adolescent narcolepsy patients showed decreased CT in bilateral frontal cortex and left precuneus. Adolescent narcolepsy demonstrated increased gyrification in left occipital lobe, left precuneus, and right fusiform but decreased gyrification in left postcentral gyrus, whereas adult narcolepsy exhibited increased gyrification in left temporal lobe and right frontal cortex. Furthermore, sleepiness severity was associated with altered CT and gyrification. Increased gyrification was associated with reduced long-range functional connectivity. In adolescent patients, those with more severe sleepiness showed increased right postcentral gyrification. Decreased frontal and occipital gyrification was found in cases with hallucination. In adult patients, a wide range of regions showed reduced gyrification in those with adolescence-onset compared adult-onset narcolepsy patients. Particularly the frontal lobes showed altered brain morphology, being a thinner cortex and more gyri. The impact of narcolepsy on age-related brain morphological changes may remain from adolescence to young adulthood, and it was especially exacerbated in adolescence.

Regional brain metabolism differs between narcolepsy type 1 and idiopathic hypersomnia.

STUDY OBJECTIVES: Daytime sleepiness is a manifestation of multiple sleep and neurologic disorders. Few studies have assessed patterns of regional brain metabolism across different disorders of excessive daytime sleepiness. One such disorder, idiopathic hypersomnia (IH), is particularly understudied. METHODS: People with IH, narcolepsy (NT1), and non-sleepy controls underwent [18F]-fluorodeoxyglucose (FDG) positron emission tomography (PET) with electroencephalography (EEG). Participants were instructed to resist sleep and were awoken if sleep occurred. Voxel-wise parametric analysis identified clusters that significantly differed between each pair of groups, with a minimum cluster size of 100 voxels at a cluster detection threshold of p < 0.005. Correlations between glucose metabolism and sleep characteristics were evaluated. RESULTS: Participants (77% women) had IH (n = 16), NT1 (n = 14), or were non-sleepy controls (n = 9), whose average age was 33.8 (±10.7) years. Compared to controls, NT1 participants demonstrated hypermetabolism in fusiform gyrus, middle occipital gyrus, superior and middle temporal gyri, insula, cuneus, precuneus, pre- and post-central gyri, and culmen. Compared to controls, IH participants also demonstrated hypermetabolism in precuneus, inferior parietal lobule, superior and middle temporal gyri, and culmen. Additionally, IH participants demonstrated altered metabolism of the posterior cingulate. Most participants fell asleep. Minutes of N1 during uptake was significantly negatively correlated with metabolism of the middle temporal gyrus. CONCLUSION: NT1 and IH demonstrate somewhat overlapping, but distinct, patterns of regional metabolism.

Neuroimaging of Narcolepsy and Primary Hypersomnias.

Advances in neuroimaging open up the possibility for new powerful tools to be developed that potentially can be applied to clinical populations to improve the diagnosis of neurological disorders, including sleep disorders. At present, the diagnosis of narcolepsy and primary hypersomnias is largely limited to subjective assessments and objective measurements of behavior and sleep physiology. In this review, we focus on recent neuroimaging findings that provide insight into the neural basis of narcolepsy and the primary hypersomnias Kleine-Levin syndrome and idiopathic hypersomnia. We describe the role of neuroimaging in confirming previous genetic, neurochemical, and neurophysiological findings and highlight studies that permit a greater understanding of the symptoms of these sleep disorders. We conclude by considering some of the remaining challenges to overcome, the existing knowledge gaps, and the potential role for neuroimaging in understanding the pathogenesis and clinical features of narcolepsy and primary hypersomnias.

Resting-state brain network topological properties and the correlation with neuropsychological assessment in adolescent narcolepsy.

STUDY OBJECTIVES: To evaluate functional connectivity and topological properties of brain networks, and to investigate the association between brain topological properties and neuropsychiatric behaviors in adolescent narcolepsy. METHODS: Resting-state functional magnetic resonance imaging (fMRI) and neuropsychological assessment were applied in 26 adolescent narcolepsy patients and 30 healthy controls. fMRI data were analyzed in three ways: group independent component analysis and a graph theoretical method were applied to evaluate topological properties within the whole brain. Lastly, network-based statistics was utilized for group comparisons in region-to-region connectivity. The relationship between topological properties and neuropsychiatric behaviors was analyzed with correlation analyses. RESULTS: In addition to sleepiness, depressive symptoms and impulsivity were detected in adolescent narcolepsy. In adolescent narcolepsy, functional connectivity was decreased between regions of the limbic system and the default mode network (DMN), and increased in the visual network. Adolescent narcolepsy patients exhibited disrupted small-world network properties. Regional alterations in the caudate nucleus (CAU) and posterior cingulate gyrus were associated with subjective sleepiness and regional alterations in the CAU and inferior occipital gyrus were associated with impulsiveness. Remodeling within the salience network and the DMN was associated with sleepiness, depressive feelings, and impulsive behaviors in narcolepsy. CONCLUSIONS: Alterations in brain connectivity and regional topological properties in narcoleptic adolescents were associated with their sleepiness, depressive feelings, and impulsive behaviors.

Localizing deficits in white matter tracts of patients with narcolepsy with cataplexy: tract-specific statistical analysis.

White matter alterations related to hypocretin pathway have been less evaluated in patients who have narcolepsy with cataplexy (NC), as compared to the identified exploration of gray matter and have varied among structural brain magnetic resonance imaging studies. The aim of this study was to investigate the disruption of specific white matter tracts in drug-naïve patients with NC, by using a tract-specific statistical analysis (TSSA). Forty drug-naïve NC patients with cataplexy and 42 heathy controls were enrolled in the study. All participants completed diffusion weighted imaging, polysomnography, and neuropsychological testing. At that time, we automatically identified fourteen major fiber tracts using diffusion tensor imaging techniques and analyzed the group comparison of fractional anisotropy (FA) values for each tract between the NC and controls, controlling for the participant's age and gender. The mean age of the NC patients was 26.9 years and the onset age of daytime sleepiness and cataplexy was 16.7 years and 19.9 years, respectively. Relative to the controls, the NC patients showed that there were identified decreased FA values in the bilateral inferior fronto-occipital fasciculus (IFO). The Epworth sleepiness scale was positively correlated with FA values for the left IFO and right cingulate. The REM sleep latency was positively correlated with FA values for the left IFO, cingulate, and uncinate fasciculus in patients. This TSSA study revealed disintegration of the IFO in the NC patients and suggested that disintegration of WM tracts connected to the frontal cortex contributes to clinical manifestations of narcolepsy.

A five-year longitudinal study reveals progressive cortical thinning in narcolepsy and faster cortical thinning in relation to early-onset.

Narcolepsy with cataplexy is characterized by excessive daytime sleepiness, cataplexy, and other REM sleep phenomena. Previous MRI studies were cross-sectional in design and could not adequately address if disease progression leads the brain structural abnormalities in narcolepsy. Our analysis in patients using longitudinally collected brain MRIs (n = 17; 2 scans per patient; scan interval: 4.7 ± 1.9 years) revealed widespread progressive cortical thinning in bilateral dorsolateral frontal and fusiform cortices, right anterior cingulate (corrected p < 0.05). Cross-sectional analyses showed faster progressive cortical thinning in patients than controls (n = 83, one scan per subject available), which we confirmed significant in the analysis of a small-set of longitudinal control data (n = 10). The pattern of progressive thinning in patients was overlapped well with those found in structural and functional studies of narcolepsy. We also found a faster progression of cortical thinning and worse disease severity (decreased sleep efficiency, increased sleep latency and arousal index) over time in a subgroup of patients with earlier disease onset (n = 9, onset age: 15.9 ± 2.5 years old) compared to later disease onset (n = 8, 25.3 ± 4.9). The faster progressive cortical thinning and worse disease severity over time in the patients with early-onset suggest compelling evidence of disease progression existing in this phenotype of narcolepsy syndrome. Our result based on a small dataset, however, demands a more careful investigation of the underlying mechanism.

Widespread white matter connectivity abnormalities in narcolepsy type 1: A diffusion tensor imaging study.

Narcolepsy type 1 is caused by a selective loss of hypothalamic hypocretin-producing neurons, resulting in severely disturbed sleep-wake control and cataplexy. Hypocretin-producing neurons project widely throughout the brain, influencing different neural networks. We assessed the extent of microstructural white matter organization and brain-wide structural connectivity abnormalities in a homogeneous group of twelve drug-free patients with narcolepsy type 1 and eleven matched healthy controls using diffusion tensor imaging with multimodal analysis techniques. First, tract-based spatial statistics (TBSS) was carried out using fractional anisotropy (FA) and mean, axial and radial diffusivity (MD, AD, RD). Second, quantitative analyses of mean FA, MD, AD and RD were conducted in predefined regions-of-interest, including sleep-wake regulation-related, limbic and reward system areas. Third, we performed hypothalamus-seeded tractography towards the thalamus, amygdala and midbrain. TBSS analyses yielded brain-wide significantly lower FA and higher RD in patients. Localized significantly lower FA and higher RD in the left ventral diencephalon and lower AD in the midbrain, were seen in patients. Lower FA was also found in patients in left hypothalamic fibers connecting with the midbrain. No significant MD and AD differences nor a correlation with disease duration were found. The brain-wide, localized ventral diencephalon (comprising the hypothalamus and different sleep- and motor-related nuclei) and hypothalamic connectivity differences clearly show a heretofore underestimated direct and/or indirect effect of hypocretin deficiency on microstructural white matter composition, presumably resulting from a combination of lower axonal density, lower myelination and/or greater axon diameter.

Neuroimaging correlates of narcolepsy with cataplexy: A systematic review.

Recent developments in neuroimaging techniques have advanced our understanding of biological mechanisms underpinning narcolepsy. We used MEDLINE to retrieve neuroimaging studies to compare patients with narcolepsy and healthy controls. Thirty-seven studies were identified and demonstrated several replicated abnormalities: (1) gray matter reductions in superior frontal, superior and inferior temporal, and middle occipital gyri, hypothalamus, amygdala, insula, hippocampus, cingulate cortex, thalamus, and nucleus accumbens, (2) decreased fractional anisotropy in white matter of fronto-orbital and cingulate area, (3) reduced brain metabolism or cerebral blood flow in middle and superior frontal, and cingulate cortex (4) increased activity in inferior frontal gyri, insula, amygdala, and nucleus accumbens, and (5) N-acetylaspartate/creatine-phosphocreatine level reduction in hypothalamus. In conclusion, all the replicated findings are still controversial due to the limitations such as heterogeneity or size of the samples and lack of multimodal imaging or follow-up. Thus, future neuroimaging studies should employ multimodal imaging methods in a large sample size of patients with narcolepsy and consider age, duration of disease, age at onset, severity, human leukocyte antigen type, cerebrospinal fluid hypocretin levels, and medication intake in order to elucidate possible neuroimaging characteristic of narcolepsy and identify therapeutic targets.