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During its pre-motor stage, Parkinson’s disease (PD) presents itself with a multitude of non-motor symptoms with different degrees of specificity and sensitivity. The most important among them are REM sleep behavior disorder (RBD) and olfactory dysfunction. RBD is a parasomnia characterized by the loss of REM sleep muscle atonia and dream-enacting behaviors. Olfactory dysfunction in individuals with prodromal PD is usually described as hyposmia (reduced sense of smell) or anosmia (complete loss of olfactory function). These symptoms can precede the full expression of motor symptoms by decades. A close comprehension of these symptoms and the underlying mechanisms may enable early screening as well as interventions to improve patients’ quality of life. Therefore, these symptoms have unmatched potential for identifying PD patients in prodromal stages, not only allowing early diagnosis but potentially opening a window for early, possibly disease-modifying intervention. However, they come with certain challenges. This review addresses some of the key opportunities and pitfalls of both RBD and olfactory dysfunction as early markers of PD.

During its pre-motor stage, Parkinson’s disease (PD) presents itself with a multitude of non-motor symptoms with different degrees of specificity and sensitivity. The most important among them are REM sleep behavior disorder (RBD) and olfactory dysfunction. RBD is a parasomnia characterized by the loss of REM sleep muscle atonia and dream-enacting behaviors. Olfactory dysfunction in individuals with prodromal PD is usually described as hyposmia (reduced sense of smell) or anosmia (complete loss of olfactory function). These symptoms can precede the full expression of motor symptoms by decades. A close comprehension of these symptoms and the underlying mechanisms may enable early screening as well as interventions to improve patients’ quality of life. Therefore, these symptoms have unmatched potential for identifying PD patients in prodromal stages, not only allowing early diagnosis but potentially opening a window for early, possibly disease-modifying intervention. However, they come with certain challenges. This review addresses some of the key opportunities and pitfalls of both RBD and olfactory dysfunction as early markers of PD.

Abnormalities in cortical sources of resting-state eyes closed electroencephalographic (rsEEG) rhythms recorded by hospital settings (10-20 montage) with 19 scalp electrodes characterized Alzheimer's disease (AD) from preclinical to dementia stages. An intriguing rsEEG application is the monitoring and evaluation of AD progression in large populations with few electrodes in low-cost devices. Here we evaluated whether the above-mentioned abnormalities can be observed from fewer scalp electrodes in patients with mild cognitive impairment due to AD (ADMCI). Clinical and rsEEG data acquired in hospital settings (10-20 montage) from 75 ADMCI participants and 70 age-, education-, and sex-matched normal elderly controls (Nold) were available in an Italian-Turkish archive (PDWAVES Consortium; www.pdwaves.eu). Standard spectral fast fourier transform (FFT) analysis of rsEEG data for individual delta, theta, and alpha frequency bands was computed from 6 monopolar scalp electrodes to derive bipolar C3-P3, C4-P4, P3-O1, and P4-O2 markers. The ADMCI group showed increased delta and decreased alpha power density at the C3-P3, C4-P4, P3-O1, and P4-O2 bipolar channels compared to the Nold group. Increased theta power density for ADMCI patients was observed only at the C3-P3 bipolar channel. Best classification accuracy between the ADMCI and Nold individuals reached 81% (area under the receiver operating characteristic curve) using Alpha2/Theta power density computed at the C3-P3 bipolar channel. Standard rsEEG power density computed from six posterior bipolar channels characterized ADMCI status. These results may pave the way toward diffuse clinical applications in health monitoring of dementia using low-cost EEG systems with a strict number of electrodes in lower- and middle-income countries.

Cognitive impairment is frequent in Parkinson’s disease (PD) and several neurotransmitter changes have been reported since the time of diagnosis, although seldom investigated altogether in the same patient cohort. Our aim was to evaluate the association between neurotransmitter impairment, brain metabolism, and cognition in a cohort of de novo, drug-naïve PD patients. We retrospectively selected 95 consecutive drug-naïve PD patients (mean age 71.89±7.53) undergoing at the time of diagnosis a brain [18F]FDG-PET as a marker of brain glucose metabolism and proxy measure of neurodegeneration, [123I]FP-CIT-SPECT as a marker and dopaminergic deafferentation in the striatum and frontal cortex, as well as a marker of serotoninergic deafferentation in the thalamus, and quantitative electroencephalography (qEEG) as an indirect measure of cholinergic deafferentation. Patients also underwent a complete neuropsychological test battery. Positive correlations were observed between (i) executive functions and left cerebellar cortex metabolism, (ii) prefrontal dopaminergic tone and working memory (r = 0.304, p = 0.003), (iii) qEEG slowing in the posterior leads and both memory (r = 0.299, p = 0.004) and visuo-spatial functions (r = 0.357, p <  0.001). Conclusions:In subjects with PD, the impact of regional metabolism and diffuse projection systems degeneration differs across cognitive domains. These findings suggest possible tailored approaches to the treatment of cognitive deficits in PD.

The management of drug‐resistant patients with focal epilepsy is often challenging. Surgery is recognised as a useful and effective treatment option. The identification of the epileptogenic zone relies on the integration of clinical, neurophysiological, and neuroimaging findings. The role of non‐invasive functional neuroimaging techniques has been reported to add diagnostic accuracy to first‐line evaluations, avoiding invasive presurgical examinations in selected cases. In this view, we report the case of a 16‐year‐old male suffering from drug‐resistant focal epilepsy with episodes rarely evolving to a bilateral tonic‐clonic seizure. Conventional 1.5T and 3T MRI were considered uninformative. Based on electro‐clinical data, focal cortical dysplasia was suspected. The epileptogenic zone was identified with the integration of further non‐invasive functional neuroimaging techniques ([18F]‐fluorodeoxyglucose positron emission tomography and arterial spin labelling), where electrical source imaging played the main role. All techniques pointed towards a cortical region, where a 7T brain MRI identified a signal alteration consistent with focal cortical dysplasia. A tailored resection of the lesion located in the inferior frontal sulcus was performed, guided by intraoperative electrocorticography (strip and depth electrodes). Postoperative seizure freedom was achieved. The histopathology confirmed the suspicion of focal cortical dysplasia type IIa. With this case report, we highlight the importance of a multimodal approach in the presurgical evaluation of candidates for epilepsy surgery, which, in selected cases, may allow invasive procedures, such as stereo‐EEG, to be avoided in the investigation of the epileptogenic zone. Moreover, we underline the pivotal role of EEG source imaging, especially when focal cortical dysplasia is suspected.

Graphical Abstract

The study of dementia and epilepsy may provide particular insight into behavioural alterations. We describe a rare case of ictal aggressive behaviour in a patient with focal epilepsy associated with a non‐dominant dorso‐lateral prefrontal lesion. During focal seizures, our patient showed intense agitation and anger, for a long time misinterpreted as psychogenic attacks, which disappeared after epilepsy surgery. The defined anatomical origin of such ictal emotional behaviour is not fully understood, however, the dorso‐lateral prefrontal area appears to correlate less frequently with aggressiveness compared to the antero‐mesial area. We describe the electroclinical data of our patient and provide a brief review of the mechanisms underlying aggressive conduct in epilepsy and dementia. An understanding of this mechanism could help to clarify the neural basis and treatment of violence associated with these and other neurological disorders. [Published with video sequence].

Background: Early differentiation between Alzheimers disease (AD) and Dementia with Lewy Bodies (DLB) is important for accurate prognosis, as DLB patients typically show faster disease progression. Cortical neural networks, necessary for human cognitive function, may be disrupted differently in DLB and AD patients, allowing diagnostic differentiation between AD and DLB. Objective: This proof-of-concept study assessed whether the application of machine learning techniques to data derived from resting-state electroencephalographic (rsEEG) rhythms (discriminant sensor power, 19 electrodes) and source connectivity (between five cortical regions of interest) allowed differentiation between DLB and AD. Methods: Clinical, demographic, and rsEEG datasets from DLB patients (N=30), AD patients (N=30), and control seniors (NOld, N=30), matched for age, sex, and education, were taken from our international database. Individual (delta, theta, alpha) and fixed (beta) rsEEG frequency bands were included. The rsEEG features for the classification task were computed at both sensor and source levels. The source level was based on eLORETA freeware toolboxes for estimating cortical source activity and linear lagged connectivity. Fluctuations of rsEEG recordings (band-pass waveform envelopes of each EEG rhythm) were also computed at both sensor and source levels. After blind feature reduction, rsEEG features served as input to support vector machine (SVM) classifiers. Discrimination of individuals from the three groups was measured with standard performance metrics (accuracy, sensitivity, and specificity). Results: The trained SVM two-class classifiers showed classification accuracies of 97.6% for NOld vs. AD, 99.7% for NOld vs. DLB, and 97.8% for AD vs. DLB. Three-class classifiers (AD vs. DLB vs. NOld) showed classification accuracy of 94.79%. Conclusion: These promising preliminary results should encourage future prospective and longitudinal cross-validation studies using higher resolution EEG techniques and harmonized clinical procedures to enable the clinical application of these machine learning techniques.

Theory of mind (ToM) deficit is a frequent finding in subjects with neurological and psychiatric conditions. While a number of brain regions play a role in ToM, to date the contribution of the diffuse projection systems is less understood.

ABSTRACTIntroduction: Obstructive sleep apneas are a frequent clinical condition in which there are momentary interruptions or reductions in breathing activity. To date, the gold standard therapy is the use of Continous Positive Airway Pressure (CPAP). But, due to the relatevely high frequency of poor compliant patients, there is the need to research possible pharmacological treatments for obstructive apnea (OSA).Areas covered: A recent study divided OSA into four major phenotypes. With this characterization in hand, the authors have reviewed the pharmacological treatments present to date according to the different phenotypes in which they could be used. Afterwards, they analyzed the efficacy of different medicaments for the therapy of the residual (despite CPAP treatment) excessive day-time sleepiness (EDS) that often afflicts OSA’ patients.Expert opinion: Different drug classes have been evaluated, with some positive results. However, there is still the need to better define treatment strategies for every single phenotype. This underlines the importance to avoid considering the pathology like a single entity without any differences between each single form. The authors are concerned about the risk that, treating only EDS, patients could reduce their compliance to CPAP, thus not reducing the cardiovascular risk associated with OSA.

Idiopathic REM sleep behavior disorder (iRBD) often precedes Parkinson’s disease (PD) and other alpha-synucleinopathies. The aim of the study is to investigate brain glucose metabolism of patients with RBD and PD by means of a multidimensional scaling approach, using18F-FDG-PET as a biomarker of synaptic function. Thirty-six iRBD patients (64.1±6.5 y, 32 M), 72 PD patients, and 79 controls (65.6±9.4 y, 53 M) underwent brain 18F-FDG-PET. PD patients were divided according to the absence (PD, 32 subjects; 68.4±8.5 y, 15 M) or presence (PDRBD, 40 subjects; 71.8±6.6 y, 29 M) of RBD. 18F-FDG-PET scans were used to independently discriminate subjects belonging to four categories: controls (RBD no, PD no), iRBD (RBD yes, PD no), PD (RBD no, PD yes) and PDRBD (RBD yes, PD yes). The discriminant analysis was moderately accurate in identifying the correct category. This is because the model mostly confounds iRBD and PD, thus the intermediate classes. Indeed, iRBD, PD and PDRBD were progressively located at increasing distance from controls and are ordered along a single dimension (principal coordinate analysis) indicating the presence of a single flux of variation encompassing both RBD and PD conditions. Data-driven approach to brain 18F-FDG-PET showed only moderate discrimination between iRBD and PD patients, highlighting brain glucose metabolism heterogeneity among such patients. iRBD should be considered as a marker of an ongoing condition that may be picked-up in different stages across patients and thus express different brain imaging features and likely different clinical trajectories.

Background/Objective: Idiopathic REM sleep behavior disorder (iRBD) often precedes Parkinson’s disease (PD) and other alpha-synucleinopathies. The aim of the study is to investigate brain glucose metabolism of patients with RBD and PD by means of a multidimensional scaling approach, using18F-FDG-PET as a biomarker of synaptic function.Methods: Thirty-six iRBD patients (64.1±6.5 y, 32 M), 72 PD patients, and 79 controls (65.6±9.4 y, 53 M) underwent brain 18F-FDG-PET. PD patients were divided according to the absence (PD, 32 subjects; 68.4±8.5 y, 15 M) or presence (PDRBD, 40 subjects; 71.8±6.6 y, 29 M) of RBD. 18F-FDG-PET scans were used to independently discriminate subjects belonging to four categories: controls (RBD no, PD no), iRBD (RBD yes, PD no), PD (RBD no, PD yes) and PDRBD (RBD yes, PD yes).Results: The discriminant analysis was moderately accurate in identifying the correct category. This is because the model mostly confounds iRBD and PD, thus the intermediate classes. Indeed, iRBD, PD and PDRBD were progressively located at increasing distance from controls and are ordered along a single dimension (principal coordinate analysis) indicating the presence of a single flux of variation encompassing both RBD and PD conditions.Conclusion: Data-driven approach to brain 18F-FDG-PET showed only moderate discrimination between iRBD and PD patients, highlighting brain glucose metabolism heterogeneity among such patients. iRBD should be considered as a marker of an ongoing condition that may be picked-up in different stages across patients and thus express different brain imaging features and likely different clinical trajectories.

Purpose Dry Eye Disease (DED) is regarded as the most common ocular surface disease worldwide, entailing symptoms that have a major impact on the physical and psychological well-being of DED patients. In this context, the impact of sleep quality on DED has recently attracted attention. Indeed, although little is known about the mechanisms underlying the relationship between sleep and ocular surface diseases, recent evidence suggests that a reciprocal relationship exists between sleep quality and DED. Aim of the study was to investigate such relationship by means of both survey-based and instrumental analysis in a large population.Patients and methods The present cross-sectional study included 1182 DED patients who completed the Insomnia Severity Index (ISI) and the Ocular Surface Disease Index (OSDI) questionnaires. Moreover, tear break-up time (TBUT) and ocular surface staining (OSS) data of included patients were collected by physicians.Results According to the findings of this study, in DED patients, the severity of dry eye symptoms and signs, assessed by OSDI score, TBUT, and ocular surface staining, is associated with more severe insomnia symptoms. Furthermore, higher severity of DED symptoms seems to be associated with the occurrence of nocturnal awakenings rather than with problems in falling asleep.Conclusions Present work contributes to the understanding of the complex relationship between DED and insomnia by showing that in a large population of DED patients, the more severe the insomnia, the more severe the DED symptoms and signs.

REM sleep behavior disorder (RBD) can be induced by antidepressants, especially serotonin reuptake inhibitors (SSRI), thus a role of the serotonergic system in the pathogenesis of RBD has been proposed. However, the serotonergic system integrity in idiopathic RBD (iRBD) is still unknown. We aimed to study brain stem serotonergic system integrity, by means of (123)I-FP-CIT-SPECT, in a group of iRBD patients as compared to normal subjects.

Metabolic connectivity analysis of resting 18F-FDG PET is based on the assumption that brain regions whose metabolism is significantly correlated at rest are functionally associated and that the strength of the association is proportional to the magnitude of the correlation coefficient. Therefore, this method could be used to evaluate connectivity networks independently on the basis of performance in specific tasks. Published studies have provided evidence that metabolic connectivity substantially overlaps underlying anatomical pathways and depends on the location of the analyzed regions, but is not influenced by their size. The present review focuses on the methods and meaning of resting inter-regional correlation analysis of cerebral metabolic rate of glucose consumption in Alzheimer’s disease. Accordingly, we describe the evolution of analytical tools from the correlation with a single region of interest to a voxel-based statistical parametric mapping-based approach. We also discuss the pathophysiological implications of metabolic connectivity studies both for Alzheimer-related disconnection syndrome and for default-mode network impairment and compensation mechanisms.

To search for a specific neuropsychological profile in idiopathic REM sleep behavior disorder (iRBD), able to predict the onset of neurodegenerative disorders.