From data to decisions: AI and functional connectivity for diagnosis, prognosis, and recovery prediction in stroke.

Stroke is a severe medical condition which may lead to permanent disability conditions. The initial 8 weeks following a stroke are crucial for rehabilitation, as most recovery occurs during this period. Personalized approaches and predictive biomarkers are needed for tailored rehabilitation. In this context, EEG brain connectivity and Artificial Intelligence (AI) can play a crucial role in diagnosing and predicting stroke outcomes efficiently. In the present study, 127 patients with subacute ischemic lesions and 90 age- and gender-matched healthy controls were enrolled. EEG recordings were obtained from each participant within 15 days of stroke onset. Clinical evaluations were performed at baseline and at 40-days follow-up using the National Institutes of Health Stroke Scale (NIHSS). Functional connectivity analysis was conducted using Total Coherence (TotCoh) and Small Word (SW). Quadratic support vector machines (SVM) algorithms were implemented to classify healthy subjects compared to stroke patients (Healthy vs Stroke), determine the affected hemisphere (Left vs Right Hemisphere), and predict functional recovery (Functional Recovery Prediction). In the classification for Functional Recovery Prediction, an accuracy of 94.75%, sensitivity of 96.27% specificity of 92.33%, and AUC of 0.95 were achieved; for Healthy vs Stroke, an accuracy of 99.09%, sensitivity of 100%, specificity of 98.46%, and AUC of 0.99 were achieved. For Left vs Right Hemisphere classification, accuracy was 86.77%, sensitivity was 91.44%, specificity was 80.33%, and AUC was 0.87. These findings highlight the potential of utilizing functional connectivity measures based on EEG in combination with AI algorithms to improve patient outcomes by targeted rehabilitation interventions.

Neuropsychological and electrophysiological measurements for diagnosis and prediction of dementia: a review on Machine Learning approach.

INTRODUCTION: Emerging and advanced technologies in the field of Artificial Intelligence (AI) represent promising methods to predict and diagnose neurodegenerative diseases, such as dementia. By using multimodal approaches, Machine Learning (ML) seems to provide a better understanding of the pathological mechanisms underlying the onset of dementia. The purpose of this review was to discuss the current ML application in the field of neuropsychology and electrophysiology, exploring its results in both prediction and diagnosis for different forms of dementia, such as Alzheimer's disease (AD), Vascular Dementia (VaD), Dementia with Lewy bodies (DLB), and Frontotemporal Dementia (FTD). METHODS: Main ML-based papers focusing on neuropsychological assessments and electroencephalogram (EEG) studies were analyzed for each type of dementia. RESULTS: An accuracy ranging between 70 % and 90 % or even more was observed in all neurophysiological and electrophysiological results trained by ML. Among all forms of dementia, the most significant findings were observed for AD. Relevant results were mostly related to diagnosis rather than prediction, because of the lack of longitudinal studies with appropriate follow-up duration. However, it remains unclear which ML algorithm performs better in diagnosing or predicting dementia. CONCLUSIONS: Neuropsychological and electrophysiological measurements, together with ML analysis, may be considered as reliable instruments for early detection of dementia.

Phantom limb syndrome: from pathogenesis to treatment. A narrative review.

Phantom Limb Syndrome (PLS) can be defined as the disabling or painful sensation of the presence of a body part that is no longer present after its amputation. Anatomical changes involved in Phantom Limb Syndrome, occurring at peripheral, spinal and brain levels and include the formation of neuromas and scars, dorsal horn sensitization and plasticity, short-term and long-term modifications at molecular and topographical levels. The molecular reorganization processes of Phantom Limb Syndrome include NMDA receptors hyperactivation in the dorsal horn of the spinal column leading to inflammatory mechanisms both at a peripheral and central level. At the brain level, a central role has been recognized for sodium channels, BDNF and adenosine triphosphate receptors. In the paper we discuss current available pharmacological options with a final overview on non-pharmacological options in the pipeline.

Search in the Periphery for Potential Inflammatory Biomarkers of Dementia with Lewy Bodies and Alzheimer's Disease.

Background: Neuroinflammation, with altered peripheral proinflammatory cytokine production, plays a major role in the pathogenesis of neurodegenerative diseases, such as Alzheimer's disease (AD), while the role of inflammation in dementia with Lewy bodies (DLB) is less known and the results of different studies are often in disagreement. Objective: The present study aimed to investigate the levels of TNFα and IL-6 in serum and supernatants, and the related DNA methylation in patients affected by DLB and AD compared to healthy controls (HCs), to clarify the role of epigenetic mechanisms of DNA promoter methylation on of pro-inflammatory cytokines overproduction. Methods: Twenty-one patients with DLB and fourteen with AD were frequency-matched for age and sex with eleven HCs. Clinical evaluation, TNFα and IL-6 gene methylation status, cytokine gene expression levels and production in serum and peripheral blood mononuclear cell (PBMC) supernatants were performed. Results: In AD and DLB patients, higher serum levels of IL-6 and TNFα were detected than in HCs. Differences in LPS-stimulated versus spontaneous PBMCs were observed between DLB, AD, and HC in the levels of TNFα (p = 0.027) and IL-6 (p < 0.001). Higher levels were also revealed for sIL-6R in DLB (p < 0.001) and AD (p < 0.001) in comparison with HC.DNA hypomethylation in IL-6 and TNFα CpG promoter sites was detected for DLB and AD patients compared to the corresponding site in HCs. Conclusions: Our preliminary study documented increased levels of IL-6 and TNFα in DLB and AD patients to HCs. This overproduction can be due to epigenetic mechanisms regarding the hypomethylation of DNA promoters.

Real-life management of patients with mild cognitive impairment: an Italian survey.

BACKGROUND: Mild cognitive impairment (MCI) is a syndrome with heterogeneous underlying causes and different rates of disease progression, whose clinical heterogeneity leads to a wide variation in diagnostic and therapeutic approaches in clinical practice. The lack of uniform practical recommendations on diagnostic workup and treatment for MCI patients hinders optimal management of these patients, worsening their prognosis. Standardized guidelines for the investigation and follow-up of MCI are therefore urgently required. AIM: Aim of our study was to assess the diagnostic and therapeutic approach to MCI patients in the setting of Italian Memory Clinics. METHODS: A survey was delivered to a sample of Italian neurologists through two different phases: a first exploratory phase recording general information about the usual clinical management of patients with MCI, and a subsequent operative phase assessing the practical diagnostic and therapeutic decisions taken in a real life setting to manage subjects with MCI. RESULTS: A total of 121 neurologists participated to the first phase of the survey and 203 patients were enrolled in the second phase. Information gathered in the first phase of the survey highlighted a non-uniform use of diagnostic criteria and procedures for MCI, as well as a very heterogeneous therapeutic strategy among Italian neurologists. In the second phase, recorded data on diagnostic and therapeutic approach confirmed the large variability observed in the first phase of the survey. CONCLUSIONS: The results of our study reflect a suboptimal management of MCI patients in Italy and highlight the need of standardized diagnostic and therapeutic approaches for this condition.

Cognitive resilience/reserve: Myth or reality? A review of definitions and measurement methods.

INTRODUCTION: This review examines the concept of cognitive reserve (CR) in relation to brain aging, particularly in the context of dementia and its early stages. CR refers to an individual's ability to maintain or regain cognitive function despite brain aging, damage, or disease. Various factors, including education, occupation complexity, leisure activities, and genetics are believed to influence CR. METHODS: We revised the literature in the context of CR. A total of 842 articles were identified, then we rigorously assessed the relevance of articles based on titles and abstracts, employing a systematic approach to eliminate studies that did not align with our research objectives. RESULTS: We evaluate-also in a critical way-the methods commonly used to define and measure CR, including sociobehavioral proxies, neuroimaging, and electrophysiological and genetic measures. The challenges and limitations of these measures are discussed, emphasizing the need for more targeted research to improve the understanding, definition, and measurement of CR. CONCLUSIONS: The review underscores the significance of comprehending CR in the context of both normal and pathological brain aging and emphasizes the importance of further research to identify and enhance this protective factor for cognitive preservation in both healthy and neurologically impaired older individuals. HIGHLIGHTS: This review examines the concept of cognitive reserve in brain aging, in the context of dementia and its early stages. We have evaluated the methods commonly used to define and measure cognitive reserve. Sociobehavioral proxies, neuroimaging, and electrophysiological and genetic measures are discussed. The review emphasizes the importance of further research to identify and enhance this protective factor for cognitive preservation.

Combined 18F-FDG PET-CT markers in dementia with Lewy bodies.

INTRODUCTION: 18F-Fluoro-deoxyglucose-positron emission tomography (FDG-PET) is a supportive biomarker in dementia with Lewy bodies (DLB) diagnosis and its advanced analysis methods, including radiomics and machine learning (ML), were developed recently. The aim of this study was to evaluate the FDG-PET diagnostic performance in predicting a DLB versus Alzheimer's disease (AD) diagnosis. METHODS: FDG-PET scans were visually and semi-quantitatively analyzed in 61 patients. Radiomics and ML analyses were performed, building five ML models: (1) clinical features; (2) visual and semi-quantitative PET features; (3) radiomic features; (4) all PET features; and (5) overall features. RESULTS: At follow-up, 34 patients had DLB and 27 had AD. At visual analysis, DLB PET signs were significantly more frequent in DLB, having the highest diagnostic accuracy (86.9%). At semi-quantitative analysis, the right precuneus, superior parietal, lateral occipital, and primary visual cortices showed significantly reduced uptake in DLB. The ML model 2 had the highest diagnostic accuracy (84.3%). DISCUSSION: FDG-PET is a valuable tool in DLB diagnosis, having visual and semi-quantitative analyses with the highest diagnostic accuracy at ML analyses.

Research diagnostic criteria for mild cognitive impairment with Lewy bodies: A systematic review and meta-analysis.

INTRODUCTION: Operationalized research criteria for mild cognitive impairment with Lewy bodies (MCI-LB) were published in 2020. The aim of this systematic review and meta-analysis was to review the evidence for the diagnostic clinical features and biomarkers in MCI-LB set out in the criteria. METHODS: MEDLINE, PubMed, and Embase were searched on 9/28/22 for relevant articles. Articles were included if they presented original data reporting the rates of diagnostic features in MCI-LB. RESULTS: Fifty-seven articles were included. The meta-analysis supported the inclusion of the current clinical features in the diagnostic criteria. Evidence for striatal dopaminergic imaging and meta-iodobenzylguanidine cardiac scintigraphy, though limited, supports their inclusion. Quantitative electroencephalogram (EEG) and fluorodeoxyglucose positron emission tomography (PET) show promise as diagnostic biomarkers. DISCUSSION: The available evidence largely supports the current diagnostic criteria for MCI-LB. Further evidence will help refine the diagnostic criteria and understand how best to apply them in clinical practice and research. HIGHLIGHTS: A meta-analysis of the diagnostic features of MCI-LB was carried out. The four core clinical features were more common in MCI-LB than MCI-AD/stable MCI. Neuropsychiatric and autonomic features were also more common in MCI-LB. More evidence is needed for the proposed biomarkers. FDG-PET and quantitative EEG show promise as diagnostic biomarkers in MCI-LB.

Intelligent digital tools for screening of brain connectivity and dementia risk estimation in people affected by mild cognitive impairment: the AI-Mind clinical study protocol.

More than 10 million Europeans show signs of mild cognitive impairment (MCI), a transitional stage between normal brain aging and dementia stage memory disorder. The path MCI takes can be divergent; while some maintain stability or even revert to cognitive norms, alarmingly, up to half of the cases progress to dementia within 5 years. Current diagnostic practice lacks the necessary screening tools to identify those at risk of progression. The European patient experience often involves a long journey from the initial signs of MCI to the eventual diagnosis of dementia. The trajectory is far from ideal. Here, we introduce the AI-Mind project, a pioneering initiative with an innovative approach to early risk assessment through the implementation of advanced artificial intelligence (AI) on multimodal data. The cutting-edge AI-based tools developed in the project aim not only to accelerate the diagnostic process but also to deliver highly accurate predictions regarding an individual's risk of developing dementia when prevention and intervention may still be possible. AI-Mind is a European Research and Innovation Action (RIA H2020-SC1-BHC-06-2020, No. 964220) financed between 2021 and 2026. First, the AI-Mind Connector identifies dysfunctional brain networks based on high-density magneto- and electroencephalography (M/EEG) recordings. Second, the AI-Mind Predictor predicts dementia risk using data from the Connector, enriched with computerized cognitive tests, genetic and protein biomarkers, as well as sociodemographic and clinical variables. AI-Mind is integrated within a network of major European initiatives, including The Virtual Brain, The Virtual Epileptic Patient, and EBRAINS AISBL service for sensitive data, HealthDataCloud, where big patient data are generated for advancing digital and virtual twin technology development. AI-Mind's innovation lies not only in its early prediction of dementia risk, but it also enables a virtual laboratory scenario for hypothesis-driven personalized intervention research. This article introduces the background of the AI-Mind project and its clinical study protocol, setting the stage for future scientific contributions.

EEG Abnormalities During Delirium as a Prodromal Feature of Dementia with Lewy Bodies: A Case Report.

Background: A 79-year-old woman was admitted to the Neurology Clinic of the University of Chieti-Pescara for a syncope. At admission, the occurrence of an acute stroke was ruled out. Her cognitive status was unimpaired. After three days from the hospitalization, the patient experienced an episode of mixed delirium. Objective: The present case report shows a case of delirium-onset dementia with Lewy bodies (DLB) with a specific electroencephalographic (EEG) pattern from its prodromal stage. Methods: Delirium was assessed by 4AT test. During the hospitalization, the patient underwent a quantitative EEG (QEEG) with spectral analysis. At six months from the episode of delirium, she was tested by neuropsychological evaluation, QEEG, and 18F-fluorodeoxyglucose PET/CT to assess the onset of a possible cognitive decline. Results: At baseline, the QEEG exam showed a dominant frequency (DF) in the pre-alpha band (7.5 Hz) with a dominant frequency variability (DFV) of 2 Hz. This pattern is typical of DLB at early stage. After six months, she reported attention deficits in association with cognitive fluctuation and REM sleep behavior disorder. The neurological examination revealed signs of parkinsonism. Cognitive status resulted to be impaired (MoCA = 15/30). QEEG recording confirmed the presence of a DLB-typical pattern (DF = 7.5 Hz, DFV = 2.5 Hz). The 18F-FDG-PET/CT showed a moderate bilateral posterior hypometabolism (occipital and temporal cortex), with relative sparing of the posterior cingulate cortex compared to cuneus/precuneus (Cingulate Island sign), and mild bilateral hypometabolism in frontal regions (suggestive of a DLB diagnosis). Conclusion: EEGs may represent supportive and validated biomarkers for delirium-onset prodromal DLB.

Perampanel enhances the cardiovagal tone and heart rate variability (HRV) in patients with drug-resistant temporal lobe epilepsy.

OBJECTIVE: The temporal lobe plays a central role in the regulation of the "Central Autonomic Network" and cardiovascular functions. The blockade of glutamatergic pathways in the temporal lobe affects cardio-autonomic control. Perampanel (PER) is a non-competitive agonist of the AMPA receptor. This study evaluated PER effects on cardiac autonomic control in patients affected by drug-resistant TLE (DRTLE). METHODS: We enrolled 40 adults with DRTLE treated with PER as add-on therapy (PER group) and 32 DRTLE age, sex, and seizure-frequency matched controls treated with different additional anti-seizure medication (ASM) as add-on therapy (No-PER group). HRV analysis was performed on 5-minute EKG recording in resting state before and 6-months after the introduction of add-on ASM. Linear Mixed Models (LMM) were used to analyzed HRV variables according to time (baseline and 6-months follow-up) and groups. RESULTS: At baseline no differences were detected between PER group and No-PER group according to time-domain and frequency-domain HRV parameters. At the follow-up, in PER group a multiplicative effect for the interaction between treatment and time was observed for MeanRR (ms) (p=0.03), LnRMSSD (ms) (p=0.04), LnHF (ms2) (p<0.001), HF n.u. (p=0.001), HF% (p=0.002) with increased values, and for LnLF (ms2) (p=0.001), LF n.u. (p=0.001), LF% (p=0.01), and LF/HF (p<0.001) with reduced values. The change in seizure frequency after add-on therapy was comparable between the two groups (p=0.81) CONCLUSIONS: Our data support the notion that PER increases the vagal tone in DRTLE. This activity may exert a cardioprotective effect by reducing the risk of developing cardiac arrhythmias. Furthermore, given the correlations between HRV modifications and the occurrence of SUDEP, future studies will need to test the protective effects of PER on SUDEP.

Accuracy of the clinical diagnosis of dementia with Lewy bodies (DLB) among the Italian Dementia Centers: a study by the Italian DLB study group (DLB-SINdem).

INTRODUCTION: Dementia with Lewy bodies (DLB) may represent a diagnostic challenge, since its clinical picture overlaps with other dementia. Two toolkits have been developed to aid the clinician to diagnose DLB: the Lewy Body Composite Risk Score (LBCRS) and the Assessment Toolkit for DLB (AT-DLB). We aim to evaluate the reliability of these two questionnaires, and their ability to enhance the interpretation of the international consensus diagnostic criteria. METHODS: LBCRS and AT-DLB were distributed to 135 Italian Neurological Centers for Cognitive Decline and Dementia (CDCDs), with the indication to administer them to all patients with dementia referred within the subsequent 3 months. We asked to subsequently apply consensus criteria for DLB diagnosis, to validate the diagnostic accuracy of the two toolkits. RESULTS: A total of 23 Centers joined the study; 1854 patients were enrolled. We found a prevalence of possible or probable DLB of 13% each (26% total), according to the consensus criteria. LBCRS toolkit showed good reliability, with a Cronbach alpha of 0.77, stable even after removing variables from the construct. AT-DLB toolkit Cronbach alpha was 0.52 and, after the subtraction of the "cognitive fluctuation" criterion, was only 0.31. Accuracy, sensitivity, and specificity were higher for LBCRS vs. AT-DLB. However, when simultaneously considered in the logistic models, AT-DLB showed a better performance (p < 0.001). Overall, the concordance between LBCRS positive and AT-DLB possible/probable was of 78.02% CONCLUSIONS: In a clinical setting, the LBCRS and AT-DLB questionnaires have good accuracy for DLB diagnosis.

ECG monitoring of post-stroke occurring arrhythmias: an observational study using 7-day Holter ECG.

Post-stroke arrhythmias represent a risk factor for complications and worse prognosis after cerebrovascular events. The aims of the study were to detect the rate of atrial fibrillation (AF) and other cardiac arrhythmias after acute ischemic stroke, by using a 7-day Holter ECG which has proved to be superior to the standard 24-h recording, and to evaluate the possible association between brain lesions and arrhythmias. One hundred and twenty patients with cryptogenic ischemic stroke underwent clinical and neuroimaging assessment and were monitored with a 7-day Holter ECG. Analysis of the rhythm recorded over 7 days was compared to analysis limited at the first 24 h of monitoring. 7-day Holter ECG detected AF in 4% of patients, supraventricular extrasystole (SVEB) in 94%, ventricular extrasystole (VEB) in 88%, short supraventricular runs (SVRs) in 54%, supraventricular tachycardia in 20%, and bradycardia in 6%. Compared to the first 24 h of monitoring, 7-Holter ECG showed a significant higher detection for all arrhythmias (AF p = 0.02; bradycardia p = 0.03; tachycardia p = 0.0001; SVEB p = 0.0002; VEB p = 0.0001; SVRs p = 0.0001). Patients with SVRs and bradycardia were older (p = 0.0001; p = 0.035) and had higher CHA2DS2VASc scores (p = 0.004; p = 0.026) respectively, in the comparison with patients without these two arrhythmias. An association was found between SVEB and parietal (p = 0.013) and temporal (p = 0.013) lobe lesions, whereas VEB correlated with insular involvement (p = 0.002). 7-day Holter ECG monitoring proved to be superior as compared to 24-h recording for the detection of all arrhythmias, some of which (SVEB and VEB) were associated with specific brain areas involvement. Therefore, 7-day Holter ECG should be required as an effective first-line approach to improve both diagnosis and therapeutic management after stroke.

Functional neurological disorder and somatic symptom disorder in Parkinson's disease.

The occurrence of Functional Neurological Disorder (FND) and Somatic Symptom Disorder (SSD) in PD was not commonly accepted until recently, despite some evidence that emerged in the pre and early L-Dopa era. More recently, the recognition of FND and SSD were noted to be relevant for the management of PD. FND and SSD appear early in the course of PD, often preceding motor symptoms, may interfere with treatment outcomes, often acquire psychotic features during progression, and are mixed with and often concealed by the progressive cognitive decline. We review the related features from the range of the available reports and discuss theoretical models conceived to explain the potential pathophysiological background of these disorders. Finally, we suggest that FND and SSD should be included among the non-motor symptoms of PD and be considered a prodromal feature in a subset of patients. This article is part of the Special Issue "Parkinsonism across the spectrum of movement disorders and beyond" edited by Joseph Jankovic, Daniel D. Truong and Matteo Bologna.

Muscarinic Receptors Expression in the Peripheral Blood Cells Differentiate Dementia with Lewy Bodies from Alzheimer's Disease.

BACKGROUND: Central nervous system disruption of cholinergic (ACh) signaling, which plays a major role in cognitive processes, is well documented in dementia with Lewy bodies (DLB) and Alzheimer's disease (AD). The expression of muscarinic ACh receptors type 1 and 4 (CHRM1 and CHRM4) has been reported to be altered in the brain of DLB patients. OBJECTIVE: We aim to assess the peripheral gene expression of CHRM1 and 4 in DLB as a possible marker as compared to AD and healthy control (HC) subjects. METHODS: Peripheral blood mononuclear cells were collected from 21 DLB, 13 AD, and 8 HC matched subjects. RT-PCR was performed to estimate gene expression of CHRM1 and CHRM4. RESULTS: Peripheral CHRM1 expression was higher and CHRM4 was lower in DLB and AD compared to HC, whereas both CHRM1 and CHRM4 levels were higher in AD compared to DLB patients. Receiver operating characteristics curves, with logistic regression analysis, showed that combining peripheral CHRM1 and CHRM4 levels, DLB and AD subjects were classified with an accuracy of 76.0%. CONCLUSION: Alterations of peripheral CHRM1 and CHRM4 was found in both AD and DLB patients as compared to HC. CHRM1 and CHRM4 gene expression resulted to be lower in DLB patients compared to AD. In the future, peripheral CHRM expression could be studied as a possible marker of neurodegenerative conditions associated with cholinergic deficit and a possible marker of response to acetylcholinesterase inhibitors.

Cortical network modularity changes along the course of frontotemporal and Alzheimer's dementing diseases.

Cortical network modularity underpins cognitive functions, so we hypothesized its progressive derangement along the course of frontotemporal (FTD) and Alzheimer's (AD) dementing diseases. EEG was recorded in 18 FTD, 18 AD, and 20 healthy controls (HC). In the FTD and AD patients, the EEG recordings were performed at the prodromal stage of dementia, at the onset of dementia, and three years after the onset of dementia. HC underwent three EEG recordings at 2-3-year time interval. Information flows underlying EEG activity recorded at electrode pairs were estimated by means of Mutual Information (MI) analysis. The functional organization of the cortical network was modelled by means of the Graph theory analysis on MI adjacency matrices. Graph theory analysis showed that the main hub of HC (Parietal area) was lost in FTD patients at onset of dementia, substituted by provincial hubs in frontal leads. No changes in global network organization were found in AD. Despite a progressive cognitive impairment during the FTD and AD progression, only the FTD patients showed a derangement in the cortical network modularity, possibly due to dysfunctions in frontal functional connectivity.

A Critical Review of Alien Limb-Related Phenomena and Implications for Functional Magnetic Resonance Imaging Studies.

Consensus criteria on corticobasal degeneration (CBD) include alien limb (AL) phenomena. However, the gist of the behavioral features of AL is still "a matter of debate." CBD-related AL has so far included the description of involuntary movements, frontal release phenomena (frontal AL), or asomatognosia (posterior or "real" AL). In this context, the most frequent symptoms are language and praxis deficits and cortical sensory misperception. However, asomatognosia requires, by definition, intact perception and cognition. Thus, to make a proper diagnosis of AL in the context of CBD, cognitive and language dysfunctions must be carefully verified and objectively assessed. We reviewed the current literature on AL in CBD and now propose that the generic use of the term AL should be avoided. This catchall AL term should instead be deconstructed. We propose that the term AL is appropriate to describe clinical features associated with specific brain lesions. More discrete sets of regionally bound clinical signs that depend on dysfunctions of specific brain areas need to be assessed and presented when posing the diagnosis. Thus, in our opinion, the AL term should be employed in association with precise descriptions of the accompanying involuntary movements, sensory misperceptions, agnosia-asomatognosia contents, and the presence of utilization behavior. The review also offers an overview of functional magnetic resonance imaging-based studies evaluating AL-related phenomena. In addition, we provide a complementary set of video clips depicting CBD-related involuntary movements that should not mistakenly be interpreted as signs of AL.