Sleep and wakefulness regulation is mediated by distributed interactions among thalamocortical circuits, hypothalamic orexinergic systems, and brainstem modulatory networks. Although the Edinger-Westphal nucleus is traditionally associated with parasympathetic pupillary control, its potential contribution to sleep and wakefulness regulation remains incompletely understood. We report a case of a 58-year-old male patient with excessive daytime sleepiness, bilateral ptosis with mydriasis (pupil diameter 6.0 mm), and complete loss of both direct and consensual light reflexes. The symptoms of hypersomnia disappeared and 24-hour polysomnography result was partially improved, with exception of still absence of stage 3 non-rapid eye movement sleep one month later. There was no improvement in the symptoms of oculomotor nerve paralysis and mydriasis. Thalamic and hypothalamic lesions can produce severe but partially reversible hypersomnia, likely mediated through disruption of thalamocortical and orexinergic systems. Midbrain involvement results in persistent oculomotor dysfunction. This case highlights the importance of distributed network interactions in sleep and wakefulness regulation and should be interpreted cautiously with regard to the specific role of the Edinger-Westphal nucleus.

In many real-world applications, the collected data with high dimensionality regularly also contain noise and outliers, which may result in learner model with insufficient generalization. The stochastic configuration network (SCN) is commonly applied to data analytics and achieve promising performance on industrial data modeling. However, the output weights of SCN are computed by the least-squares method, which is susceptible to noise and outliers. In this context, a novel framework of sparse generalized robust SCN (SGRSCN) is presented in this article. An arbitrary concave function is introduced in the loss function of SGRSCN that is employed to set the penalty weights for each training samples, which can reduce the negative impacts of noise and outliers to some extent. In addition, to address the architecture complexity and ill-posed problems of SCN when processing high-dimensional data, the loss function also consists of the L-2,L-p-norm (0 < p < 1) regularization term. By adjusting p, the sparse model can be obtained. Then, the alternating optimization algorithm is applied to the optimization of loss function and the convergence analysis of the optimization process is provided. Moreover, a typical concave function is selected as an example using the framework of SGRSCN. Finally, the performance of SGRSCN is evaluated on two benchmark datasets and a real-world dataset with high-dimensional features. The experimental results demonstrate the superiority of SGRSCN.

Insomnia is a prevalent sleep disorder, and for which effective therapeutic targets remain lacking. In this study, we conducted a GWAS meta-analysis on 3 datasets: ukb-b-3957, FinnGen R10, and ebi-a-GCST004695, using METAL. Building on this, we further investigated the causality of plasma proteins using a protein Mendelian randomization (MR) approach. The MR analysis utilized protein datasets from deCODE and UKB, incorporating co-localization. Reverse MR was employed to examine the potential presence of reverse causality. MAGMA was employed to investigate key proteins associated with insomnia, along with tissue enrichment analysis. The insomnia GWAS meta-analysis revealed that 250 genes exhibited statistically significant signals after FDR correction (P < .05). A total of 81 risk loci were identified (P < 5e-8), and the risk genes were predominantly enriched in tissues such as the cerebellum, cerebellar hemisphere, and prefrontal cortex. Our PW-MR analysis identified 36 proteins with replicated causal associations with insomnia. After excluding one protein (HEXIM1) due to evidence of reverse causality, we established a final list of 35 high-confidence candidate proteins. Further colocalization analysis supported a shared causal variant for several candidates, including DNPH1 and PTK7. This study identifies a robust list of plasma proteins with genetically-predicted causal links to insomnia risk. These findings offer a valuable resource for subsequent functional validation studies aimed at elucidating the molecular mechanisms underlying the disorder.

There has been a growing interest in unsupervised domain adaptation (UDA) to alleviate the data scalability issue, while the existing works usually focus on classifying independently discrete labels. However, in many tasks (e.g., medical diagnosis), the labels are discrete and successively distributed. The UDA for ordinal classification requires inducing non-trivial ordinal distribution prior to the latent space. Target for this, the partially ordered set (poset) is defined for constraining the latent vector. Instead of the typically i.i.d. Gaussian latent prior, in this work, a recursively conditional Gaussian (RCG) set is proposed for ordered constraint modeling, which admits a tractable joint distribution prior. Furthermore, we are able to control the density of content vectors that violate the poset constraint by a simple "three-sigma rule." We explicitly disentangle the cross-domain images into a shared ordinal prior induced ordinal content space and two separate source/target ordinal-unrelated spaces, and the self-training is worked on the shared space exclusively for ordinal-aware domain alignment. Extensive experiments on UDA medical diagnoses and facial age estimation demonstrate its effectiveness.

BACKGROUND:The medullary nucleus of solitary tract (NTS) and its afferents of vagus nerve have long been investigated in regulation of cortical activity and sleep promotion. However, the underlying neural circuit by which the NTS regulates electroencephalogram (EEG) and sleep remain unclear. As the NTS has a strong projection to the pontine arousal site, the parabrachial nucleus (PB), we proposed the NTS via the pontine parabrachial nucleus (PB) regulates cortical activity and sleep. METHODS:We bilaterally and directly stimulated the NTS neurons by chemogenetic approach and NTS terminals in the PB by optogenetic approach and examined changes in EEG and sleep in rats. RESULTS:Opto- and chemo-stimulation of the NTS and NTS-PB pathway altered neither sleep amounts nor patterns; however, both stimulations consistently increased EEG delta (0.5-4.0 Hz) EEG power during non-rapid-eye-movement (NREM) sleep and alpha-beta (10-30 Hz) EEG power during wake and REM sleep. CONCLUSION:Our results indicate that the NTS via its projections to the PB synchronizes low frequency EEG during NREM sleep and high frequency EEG during wake and REM sleep. This pathway may serve the neural foundation for the vagus nerve stimulation (VNS) treating cortical disorders.

The hippocampus (HPC) plays a pivotal role in fear learning and memory. Our two recent studies suggest that rapid eye movement (REM) sleep via the HPC downregulates fear memory consolidation and promotes fear extinction. However, it is not clear whether and how the dorsal and the ventral HPC regulates fear memory differently; and how the HPC in wake regulates fear memory. By chemogenetic stimulating in the HPC directly and its afferent entorhinal cortex that selectively activated the HPC in REM sleep for 3-6 h post-fear-acquisition, we found that HPC activation in REM sleep consolidated fear extinction memory. In particular, dorsal HPC (dHPC) stimulation in REM sleep virtually eliminated fear memory by enhancing fear extinction and reducing fear memory consolidation. By contrast, chemogenetic stimulating HPC afferent the supramammillary nucleus (SUM) induced 3-hr wake with HPC activation impaired fear extinction. Finally, desipramine (DMI) injection that selectively eliminated REM sleep for >6 h impaired fear extinction. Our results demonstrate that the HPC is critical for fear memory regulation; and wake HPC and REM sleep HPC have an opposite role in fear extinction of respective impairment and consolidation.

Introduction: The basal forebrain (BF) and the medial septum (MS) respectively drive neuronal activity of cerebral cortex and hippocampus (HPC) in sleep-wake cycle. Our previous studies of lesions and neuronal circuit tracing have shown that the pontine parabrachial nucleus (PB) projections to the BF and MS may be a key circuit for cortical and HPC arousal.Aims: This study aims to demonstrate that PB projections to the BF and MS activate the cerebral cortex and HPC.Results: By using chemogenetic stimulation of the BF, the PB-BF and the PB-MS pathway combined with elec-troencephalogram (EEG) Fast Fourier Transformation (FFT) analysis in rats, we demonstrated that chemogenetic stimulation of the BF or PB neurons projecting to the BF activated the cerebral cortex while chemogenetic stimulation of the MS or PB neurons projecting to the MS activated HPC activity, in sleep and wake state. These stimulations did not significantly alter sleep-wake amounts. Conclusions: Our results support that PB projections to the BF and MS specifically regulating cortical and HPC activity.

AIMS:We often experience dreams of strong irrational and negative emotional contents with postural muscle paralysis during rapid eye movement (REM) sleep, but how REM sleep is generated and its function remain unclear. In this study, we investigate whether the dorsal pontine sub-laterodorsal tegmental nucleus (SLD) is necessary and sufficient for REM sleep and whether REM sleep elimination alters fear memory.METHODS:To investigate whether activation of SLD neurons is sufficient for REM sleep induction, we expressed channelrhodopsin-2 (ChR2) in SLD neurons by bilaterally injecting AAV1-hSyn-ChR2-YFP in rats. We next selectively ablated either glutamatergic or GABAergic neurons from the SLD in mice in order to identify the neuronal subset crucial for REM sleep. We finally  investigated the role of REM sleep in consolidation of fear memory using rat model with complete SLD lesions.RESULTS:We demonstrate the sufficiency of the SLD for REM sleep by showing that photo-activation of ChR2 transfected SLD neurons selectively promotes transitions from non-REM (NREM) sleep to REM sleep in rats. Diphtheria toxin-A (DTA) induced lesions of the SLD in rats or specific deletion of SLD glutamatergic neurons but not GABAergic neurons in mice completely abolish REM sleep, demonstrating the necessity of SLD glutamatergic neurons for REM sleep. We then show that REM sleep elimination by SLD lesions in rats significantly enhances contextual and cued fear memory consolidation by 2.5 and 1.0 folds, respectively, for at least 9 months. Conversely, fear conditioning and fear memory trigger doubled amounts of REM sleep in the following night, and chemo-activation of SLD neurons projecting to the medial septum (MS) selectively enhances hippocampal theta activity in REM sleep; this stimulation immediately after fear acquisition reduces contextual and cued fear memory consolidation by 60% and 30%, respectively.CONCLUSION:SLD glutamatergic neurons generate REM sleep and REM sleep and SLD via the hippocampus particularly down-regulate contextual fear memory.

Pontine sub-laterodorsal tegmental nucleus (SLD) is crucial for REM sleep. However, the necessary role of SLD for REM sleep, cataplexy that resembles REM sleep, and emotion memory by REM sleep has remained unclear. To address these questions, we focally ablated SLD neurons using adenoviral diphtheria-toxin (DTA) approach and found that SLD lesions completely eliminated REM sleep accompanied by wake increase, significantly reduced baseline cataplexy amounts by 40% and reward (sucrose) induced cataplexy amounts by 70% and altered cataplexy EEG Fast Fourier Transform (FFT) from REM sleep-like to wake-like in orexin null (OXKO) mice. We then used OXKO animals with absence of REM sleep and OXKO controls and examined elimination of REM sleep in anxiety and fear extinction. Our resulted showed that REM sleep elimination significantly increased anxiety-like behaviors in open field test (OFT), elevated plus maze test (EPM) and defensive aggression and impaired fear extinction. The data indicate that in OXKO mice the SLD is the sole generator for REM sleep; (2) the SLD selectively mediates REM sleep cataplexy (R-cataplexy) that merges with wake cataplexy (W-cataplexy); (3) REM sleep enhances positive emotion (sucrose induced cataplexy) response, reduces negative emotion state (anxiety), and promotes fear extinction.

Alpha-synuclein induced degeneration of the midbrain substantia nigra pars compact (SNc) dopaminergic neurons causes Parkinson's disease (PD). Rodent studies demonstrate that nigrostriatal dopamine stimulates pallidal neurons which, via the topographical pallidocortical pathway, regulate cortical activity and functions. We hypothesize that nigrostriatal dopamine acting at the basal ganglia regulates cortical activity in sleep and wake state, and its depletion systemically alters electroencephalogram (EEG) across frequencies during sleep-wake state. Compared to control rats, 6-hydroxydopamine induced selective SNc lesions increased overall EEG power (positive synchronization) across 0.5-60 Hz during wake, NREM (non-rapid eye movement) sleep, and REM sleep. Application of machine learning (ML) to seven EEG features computed at a single or combined spectral bands during sleep-wake differentiated SNc lesions from controls at high accuracy. ML algorithms construct a model based on empirical data to make predictions on subsequent data. The accuracy of the predictive results indicate that nigrostriatal dopamine depletion increases global EEG spectral synchronization in wake, NREM sleep, and REM sleep. The EEG changes can be exploited by ML to identify SNc lesions at a high accuracy.

Activation of the parabrachial nucleus (PB) in the brainstem induced wakefulness in rats, suggesting which is an important nucleus that controls arousal. However, the sub-regions of PB in regulating sleep-wake cycle is still unclear. Here, we employ chemogenetics and optogenetics strategies and find that activation of the medial part of PB (MPB), but not the lateral part, induces continuous wakefulness for 10 h without sleep rebound in neither sleep amount nor the power spectra. Optogenetic activation of glutamatergic MPB neurons in sleeping rats immediately wake rats mediated by the basal forebrain (BF) and lateral hypothalamus (LH), but not the ventral medial thalamus. Most importantly, chemogenetic inhibition of PB neurons decreases wakefulness for 10 h. Conclusively, these findings indicate that the glutamatergic MPB neurons are essential in controlling wakefulness, and that MPB-BF and MPB-LH pathways are the major neuronal circuits.

In this work, we propose a domain generalization (DG) approach to learn on several labeled source domains and transfer knowledge to a target domain that is inaccessible in training. Considering the inherent conditional and label shifts, we would expect the alignment of p(x|y) and p(y). However, the widely used domain invariant feature learning (IFL) methods relies on aligning the marginal concept shift w.r.t. p(x), which rests on an unrealistic assumption that p(y) is invariant across domains. We thereby propose a novel variational Bayesian inference framework to enforce the conditional distribution alignment w.r.t. p(x|y) via the prior distribution matching in a latent space, which also takes the marginal label shift w.r.t. p(y) into consideration with the posterior alignment. Extensive experiments on various benchmarks demonstrate that our framework is robust to the label shift and the cross-domain accuracy is significantly improved, thereby achieving superior performance over the conventional IFL counterparts.

Sleep and wakefulness are promoted not by a single neural pathway but via wake or sleep-promoting nodes distributed across layers of the brain. We equate each layer with a brain region in proposing a layered subsumption model for arousal based on a computational architecture. Beyond the brainstem the layers include the diencephalon (hypothalamus, thalamus), basal ganglia, and cortex. In light of existing empirical evidence, we propose that each layer have sleep and wake computations driven by similar high-level architecture and processing units. Specifically, an interconnected wake-promoting system is suggested as driving arousal in each brain layer with the processing converging to produce the features of wakefulness. In contrast, sleep-promoting GABAergic neurons largely project to and inhibit wake-promoting neurons. We propose a general pattern of caudal wake-promoting and sleep-promoting neurons having a strong effect on overall behavior. However, while rostral brain layers have less influence on sleep and wake, through descending projections, they can subsume the activity of caudal brain layers to promote arousal. The two models presented in this work will suggest computations for the layering and hierarchy. Through dynamic system theory several hypotheses are introduced for the interaction of controllers and systems that correspond to the different populations of neurons at each layer. The models will be drawn-upon to discuss future experiments to elucidate the structure of the hierarchy that exists among the sleep-arousal architecture.

Sleep pressure that builds up gradually during the extended wakefulness results in sleep rebound. Several lines of evidence, however, suggest that wake per se may not be sufficient to drive sleep rebound and that rapid eye movement (REM) and non-rapid eye movement (NREM) sleep rebound may be differentially regulated. In this study, we investigated the relative contribution of brain versus physical activities in REM and NREM sleep rebound by four sets of experiments. First, we forced locomotion in rats in a rotating wheel for 4 hr and examined subsequent sleep rebound. Second, we exposed the rats lacking homeostatic sleep response after prolonged quiet wakefulness and arousal brain activity induced by chemoactivation of parabrachial nucleus to the same rotating wheel paradigm and tested if physical activity could rescue the sleep homeostasis. Third, we varied motor activity levels while concurrently inhibiting the cortical activity by administering ketamine or xylazine (motor inhibitor), or ketamine + xylazine mixture and investigated if motor activity in the absence of activated cortex can cause NREM sleep rebound. Fourth and finally, we manipulated cortical activity by administering ketamine (that induced active wakefulness and waking brain) alone or in combination with atropine (that selectively inhibits the cortex) and studied if cortical inhibition irrespective of motor activity levels can block REM sleep rebound. Our results demonstrate that motor activity but not cortical activity determines NREM sleep rebound whereas cortical activity but not motor activity determines REM sleep rebound.

The midbrain dopamine system via the dorsal and ventral striatum regulates a wide range of behaviors. To dissect the role of dopaminergic projections to the dorsal striatum (nigrostriatal projection) and ventral striatum (mesolimbic projection) in sleep–wake behavior, we selectively chemogenetically stimulated nigrostriatal or mesolimbic projections and examined the resulting effects on sleep in rats. Stimulation of nigrostriatal pathways increased sleep and EEG delta power, while stimulation of mesolimbic pathways decreased sleep and reduced cortical EEG power. These results indicate that midbrain dopamine signaling in the dorsal or ventral striatum promotes sleep or wake, respectively.

INTRODUCTION Fatal familial insomnia (FFI) is a serious and rare prion disease, which was first reported by Lugaresi et al. in 1986.[1] Early diagnosis of FFI might be important for early and sufficient counseling of patients and their relatives, also concerning the risk of inheritance, and potentially also for treatment studies. However, the diagnosis of FFI might be difficult because of the heterogeneity of clinical features, low sensitivity of diagnostic tests, and absence of family history. The aim of the present study was to develop a clinical scheme and diagnostic criteria for FFI based on our research and expert consensus. EPIDEMIOLOGY OF FATAL FAMILIAL INSOMNIA Up until 2016, more than hundred FFI cases from 50 families carrying the gene for FFI in the world have been reported. The majority of the cases reported were from Europe, specifically Italy, Spain, and Germany.[23] Although familial aggregation is robust in FFI, nine sporadic cases have been reported.[2] It is speculated that the annual incidence of FFI worldwide is about one out of a million people.[2] There are no gender differences among FFI patients. The mean age at onset of FFI is approximately 50 years (range, 21–62 years), and the duration of FFI ranges from 7 to 25 months.[3] In recent years, more and more FFI cases have been reported worldwide, more specifically in China. The first Chinese case was reported in a patient who emigrated from Hong Kong to Canada in 2004,[4] and the second case was reported from the Hubei province in 2005.[5] A higher number of cases have been reported since the China Creutzfeldt–Jakob disease (CJD) surveillance program was initiated in 2006. A total of 13 cases from 13 Chinese families have been documented from 2006 to 2017.[678910111213] Among Chinese patients, the age at onset ranges from 21 to 68 years. The average age at onset of FFI is similar to those reported in other countries, with a mean age of 46.5 years.[14] The clinical duration of FFI among the Chinese cases ranges from 6 to 38 months, which seems much longer than that for European patients.[15] Furthermore, it was reported that FFI is the most frequently identified genetic prion disease in China.[16] It is worth noting that more FFI cases have been reported in China than those in any other Asian regions (three cases were reported in Japan and one case in Korea),[3] suggesting a genetic susceptibility among the Han population. Because FFI is a rare disease and most information is from case reports, its prevalence and associated factors need to be clarified by more studies. ETIOLOGY AND PATHOGENESIS FFI is a genetic prion disease transmitted in an autosomal dominant pattern. It is associated with a missense GAC to AAC mutation at codon 178 of the prion protein (PRNP) gene located on chromosome 20, which leads to a substitution of asparagine for aspartic acid (D178N).[1718] This mutation is always associated with methionine at the polymorphic position 129 of the mutant allele in FFI.[19] Although highly expressed in brain tissues, the physiological function of the prion protein (PrP) remains enigmatic. The pathogenesis of FFI is considered to be due to the loss of the natural function of the PrP. This results in PrP that becomes more susceptible to transformation into an abnormal misfolded form, triggering a selective loss of neurons in the limbic thalamus and corticolimbic regions.[20] The highly selective neuronal loss is partly due to the binding of FFI toxic PrP or proteinase K-resistant prion protein (PrPres) to specific receptors, such as the limbic system-associated membrane protein (LAMP) receptor on thalamolimbic neurons.[21] Pathologically, FFI is characterized by severe and selective thalamic degeneration, especially in the mediodorsal and anterior ventral nuclei,[117] in which more than 50% of the magnocellular and parvocellular neurons are lost as observed during autopsy. In some cases, almost 80% neuronal loss was observed.[17] The other thalamic nuclei are less consistently and less severely involved. Other histopathological changes, including reactive astrogliosis in thalamic nuclei, the cerebral and cerebellar cortices, and the olives, are also found. Spongiosis of the cerebral cortex is observed in some cases, but is either moderate or sometimes absent, especially in cases with a short disease course.[20] Parchi et al.[22] reported that patients with disease duration shorter than 18 months only have minimal cortical cerebral astrogliosis and focal spongiosis in the entorhinal cortex, whereas patients with a disease duration longer than 18 months have cortical spongiosis and astrogliosis that are more widespread. Moderate atrophy of the cortex and basal ganglia has also been previously observed in FFI cases, while abnormalities are rarely detected in the spinal cord.[23] CLINICAL CHARACTERISTICS OF THE FATAL FAMILIAL INSOMNIA FFI is a hereditary autosomal dominant prion disease, which is mainly characterized by prominent sleep impairment accompanied by a series of neuropsychiatric disorders, dysautonomia, motor dysfunction, and episodes of peculiar oneiric behaviors (oneiric stupor).[24] Irregular breathing, hypnic jerks, propriospinal myoclonus at the wake-sleep transition, and quasi-purposeful limb gestures are considered to be core features of FFI. Homozygous FFI might be different from heterozygous FFI in terms of clinical severity.[17] The most prominent clinical manifestation is sleep disturbance, which includes insomnia, laryngeal stridor, sleep breath disturbance, oneiric or stuporous episodes with hallucinations and confusion, and sleep-related involuntary movements (such as hypnic jerks, restless sleep with frequent changes in body position, and twitchy nonpurposeful movement of limbs). However, FFI symptoms are variable and some FFI cases may not present with clinically significant insomnia.[2526] Rapidly progressive dementia (RPD) along with psychiatric symptoms occurs in all patients. Patients might have cognitive/amnestic deficits, spatial disorientation, and visual hallucinations. They may also display personality changes, depression, anxiety, aggressiveness, disinhibition, and listlessness.[27] The symptoms and signs of sympathetic hyperactivity (such as evening pyrexia, hypertension, increased sweating and tearing, tachycardia/tachypnea, and impotence) and somatomotor abnormalities (including pyramidal signs, myoclonus, dysarthria/dysphagia, and gait dysfunctions) occur with variable latency and worsen progressively. The prominent motor impairment is a gait dysfunction, and its severity and features may be related to duration and genotype.[28] Furthermore, husky voice was reported in 22% of FFI patients in Germany.[27] The main clinical and neurological features of FFI are summarized in Table 1.Table 1: Clinical characteristics of the FFI patientsDIAGNOSTIC STUDIES For diagnosis of FFI, the main tests with high diagnostic value include genetic analysis, brain magnetic resonance imaging (MRI), electroencephalograms (EEG), polysomnography (PSG), positron emission tomography (PET), single-photon emission tomography (SPECT), biochemical cerebrospinal fluid (CSF) analysis, and autopsy. Genetic analysis Genetically, FFI is associated with a GAC to AAC point mutation at codon 178 of PRNP resulting in the D178N substitution in combination with methionine (Met) at codon 129 in the mutated allele of PRNP (D178N-129M haplotype).[29] Brain magnetic resonance imaging Routine brain MRI (T1- and T2-weighted imaging) usually reveals nonspecific features including mild cerebral cortical atrophy and enlarged ventricles. The mean apparent diffusion coefficient value could increase in the thalamus.[30] Hyperintense signals could be detected by diffusion-weighted image (DWI) in the basal ganglia and other gray matter areas.[31] Electroencephalograms EEG usually demonstrates a diffusive excess of theta (θ) and delta (δ) frequencies. Periodic spike discharges are not found in most cases of FFI, but patients with long disease duration can transiently show periodic EEG activities in latter stages.[32] Polysomnography A key early polysomnographic sign of the disease onset is the loss of sleep spindles and K-complexes. Other polysomnographic findings include progressively shortened total sleep time, significantly reduced durations of rapid eye movement sleep and slow-wave sleep, abnormal behaviors, complex hallucinations, vivid dreams during sleep, and laryngeal sounds during sleep.[24] Positron emission tomography and single-photon emission tomography PET study typically indicated hypometabolism predominantly in the thalamus and cingulate cortex in FFI.[33] SPECT imaging showed reduced blood flow perfusion in bilateral temporal lobes, basal ganglia, and thalamus.[13] Cerebrospinal fluid analysis CSF biochemical test could be normal or show a mildly elevated protein concentration. The CSF is usually negative for 14-3-3 protein in FFI. Autopsy No FFI case involving brain biopsy case has been reported. At autopsy, severe thalamic neuronal loss and gliosis are characteristically seen in postmortem brains of FFI patients, usually without a concomitant spongiform change. The most seriously affected thalamic nuclei are the anteroventral, mediodorsal nuclei, and pulvinar.[3435] DIAGNOSIS Central clinical presentations in FFI patients can be divided into three categories [Table 1]: Cluster A – organic sleep disturbance, including insomnia, laryngeal stridor, sleep-related dyspnea, and sleep-related involuntary movements; Cluster B – RPD, with or without ataxia, pyramidal or extrapyramidal symptoms/signs, and psychiatric symptoms; and Cluster C – progressive sympathetic symptoms, including hypertension, sweating, tachycardia, irregular breathing, and dysarthria. Based on the above clinical classification, family history, and laboratory tests, we propose the following clinical diagnostic criteria algorithm for the diagnosis of FFI: (1) possible FFI, (2) probable FFI, and (3) definitive FFI. Core clinical features and possible fatal familial insomnia The organic sleep-related abnormalities (a) in addition to one or two other core features (b/c) are essential for a diagnosis of possible FFI. Organic sleep-related symptoms: Insomnia, lack of deep sleep, sleep fragmentation and reduction or loss of REM sleep, laryngeal stridor, sleep breath disturbance, and involuntary movements RPD: The presence or absence of ataxia, pyramidal or extrapyramidal symptoms or signs, and psychiatric symptoms Progressive sympathetic symptoms: Hypertension, sweating, tachycardia, and irregular breathing. Suggestive features and probable fatal familial insomnia If one or more of these suggestive features and two or more core features above are present, a diagnosis of probable FFI can be made. Positive family history of RPD and insomnia Organic insomnia, sleep-related apnea, laryngeal stridor, and involuntary movements revealed by PSG Low glucose uptake in the thalamus demonstrated by SPECT or PET imaging. Diagnostic features and definitive fatal familial insomnia If the PRNP gene test is positive, a diagnosis of definitive FFI can be confirmed. PRNP gene sequencing revealed D178N mutation with methionine polymorphism at codon 129. DIFFERENTIAL DIAGNOSIS Patients affected by CJD usually present with RPD, myoclonus, visual abnormalities, cerebellar dysfunction, pyramidal and extrapyramidal dysfunction, and akinetic mutism. DWI or fluid-attenuated inversion recovery (FLAIR) MRI shows a hyperintense signal in the caudate nucleus and putamen or at least two cortical regions. Although FFI patients may have any of these CJD symptoms, they do not fulfill the established diagnostic criteria for CJD.[181920] FFI patients are more likely to have longer disease durations, and severe insomnia and dysautonomia, and are less likely to have typical CJD-like cortical ribboning in DWI. D178N point mutation with biallelic codon 129 M on PRNP gene is the only causative mutation for FFI, while familial CJD may be caused by 22 types of point mutations, or by insertional mutations.[36] Neuropathological findings of FFI and CJD are quite different: selective thalamic gliosis and neuronal loss are core features of FFI while typical neuropathological findings of CJD include neuronal loss, gliosis, and vacuolation (or spongiform changes).[37] Gerstmann Sträussler Scheinker disease (GSS) is another prion disease that shares similar clinical manifestations with FFI. It typically presents as a subacute progressive ataxic and/or parkinsonian disorder with a later onset of cognitive impairment. The mean disease duration is around 5 years, ranging from 3 to more than 8 years. GSS has been associated with many different point mutations or insertional mutations of octapeptide repeats, and D178N has not been identified in GSS.[36] Limbic DWI or FLAIR hyperintensities can be found in up to 50% of cases.[38] Paraneoplastic and nonparaneoplastic limbic encephalitis can also present with RPD and behavior and movement disturbances. Unlike FFI, patients with paraneoplastic and nonparaneoplastic limbic encephalitis have acute/subacute onsets, and symptoms peak within days to weeks; CSF tests usually show pleocytosis and an increased protein level. The main MRI findings that allow the differentiation of encephalitis from FFI are cortical swelling, petechial hemorrhages, and patchy enhancement postcontrast agent administration in the subacute stage.[39] Antibody testing in both CSF and serum is especially crucial. CONCLUSION We attempted to establish easily applicable and reliable clinical diagnostic criteria for FFI based on our own research and the literature review. The scheme would also enable the clinical diagnosis in cases with/without available diagnostic testing. We hope that these criteria might improve the early recognition of this peculiar and rare prion disease. Financial support and sponsorship This work was supported by grants from the National Natural Science Foundation of China (No. 81470074), and the Clinical funding from Beijing Municipal Science and Technology Committee (No.Z14l107002514117). Conflicts of interest There are no conflicts of interest.

Copper accumulation in brain is common in many neurological diseases, such as Wilson’s disease. However, the effect of copper in specific brain regions remains unclear. 20 div of CuCl2 (500 μM) was injected into bilateral globus pallidus externus (GPe) in Rats. EEG/EMG and the behavior using real-time video were recorded. The sleep and movement-related parameters and the behaviors monitored by the video were analyzed and quantified by the software. For sleep, compared with the control rats, the wakefulness of copper-treated rats was significantly decreased in 24h, and the NREM was significantly increased in the light period and 24 h, while the REM did not change significantly. For the movement, compared with the control rats, the movement of copper-treated rats in the transformation period from NREM to wake was significantly increased in the light period, dark period and 24 h. The movement in the transformation period from REM to wakefulness was significantly increased in dark period. The movement of REM was not significantly changed. These data demonstrated that copper accumulation in GPe could cause movement deficits and sleep disorder, reminiscent of behavioral and sleep disorders as observed in Wilson’s disease and Parkinson’s disease. Our data suggested that GPe could be a crucial brain region involved in behavioral and sleep disorders in some neurological diseases such as Wilson’s disease and Parkinson’s disease. (Dr. Xifei Yang and Dr. Fei Qi have contributed equally to this work.) This work was supported by NSFC (the National Natural Science Foundation of China) (81673134, 81501213, 81571294), Guangdong Provincial Natural Science Foundation (2014A030313715, 2016A030313051), Guangdong Provincial Scheme of Science and Technology (To X.F.Y), and Shenzhen Special Fund Project on Strategic Emerging Industry Development(JCY20160428143433768, JCYJ20150529164656093, JCYJ20150529153646078).