A New MRI Measure to Early Differentiate Progressive Supranuclear Palsy From De Novo Parkinson's Disease in Clinical Practice: An International Study.

BACKGROUND: Enlargement of the third ventricle has been reported in atypical parkinsonism. We investigated whether the measurement of third ventricle width could distinguish Parkinson's disease (PD) from progressive supranuclear palsy (PSP). METHODS: We assessed a new MR T1-weighted measurement (third ventricle width/internal skull diameter) in a training cohort of 268 participants (98 PD, 73 PSP, 98 controls from our center) and in a testing cohort of 291 participants (82 de novo PD patients and 133 controls from the Parkinson's Progression Markers Initiative, 76 early-stage PSP from an international research group). PD diagnosis was confirmed after a 4-year follow-up. Diagnostic performance of the third ventricle/internal skull diameter was assessed using receiver operating characteristic curve with bootstrapping; the area under the curve of the training cohort was compared with the area under the curve of the testing cohort using the De Long test. RESULTS: In both cohorts, third ventricle/internal skull diameter values did not differ between PD and controls but were significantly lower in PD than in PSP patients (P < 0.0001). In PD, third ventricle/internal skull diameter values did not change significantly between baseline and follow-up evaluation. Receiver operating characteristic analysis accurately differentiated PD from PSP in the training cohort (area under the curve, 0.94; 95% CI, 91.1-97.6; cutoff, 5.72) and in the testing cohort (area under the curve, 0.91; 95% CI, 87.0-97.0; cutoff,: 5.88), validating the generalizability of the results. CONCLUSION: Our study provides a new reliable and validated MRI measurement for the early differentiation of PD and PSP. The simplicity and generalizability of this biomarker make it suitable for routine clinical practice and for selection of patients in clinical trials worldwide. © 2020 International Parkinson and Movement Disorder Society.

The impact of sexual abuse on psychopathology of patients with psychogenic nonepileptic seizures.

OBJECTIVES: In the present study, we evaluated if the presence of sexual abuse in the clinical history of patients with psychogenic non-epileptic seizures (PNES) is associated with a different psychopathological profile. MATERIALS AND METHODS: In a consecutive population of 63 PNES patients, we compared two demographically and clinically matched groups of patients with (no. 15) and without (no. 48) a history of sexual abuse using a comprehensive psychopathological assessment (Beck Depression Inventory, Hamilton Anxiety Rating Scale, Dissociative Experience Scale, Somatoform Dissociation Questionnaire, and Toronto Alexithymia Scale). RESULTS: We found that the group of patients reporting sexual abuse is characterized by higher scores on Dissociative Experience Scale (p = 0.003) and Beck Depression Inventory (p = 0.001) with respect to the other group. No significant statistical differences in Hamilton Anxiety Rating Scale (p = 0.103), Toronto Alexithymia Scale (p = 0.137), and Somatoform Dissociation Questionnaire (p = 0.486) were captured. Moreover, we found that the negative effect on dissociate symptoms was also hampered by the increasing of seizure frequency. CONCLUSIONS: This study reinforces the importance of traumatic screening in the clinical spectrum of PNES in order to implement and improve specific therapeutic strategies.

The embodiment of language in tremor-dominant Parkinson's disease patients.

According to embodied cognition, processing language with motor content involves a simulation of this content by the brain motor system. Patients with brain lesions involving the motor system are characterized by deficits in action verbs processing in the absence of dementia. We sought to assess whether action verbs interfere with the motor behavior of patients with Parkinson's disease (PD) having tremor dominant symptoms. PD tremor is considered to result from dysfunction of cortical-subcortical motor circuits driven by dopamine depletion. In addition, PD tremor is reduced during active movement execution. Therefore, likewise movement execution, the motor simulation of bodily actions predicted by the embodiment may show to be effective in modifying tremor by interfering with a dysfunctional motor system. Here, we asked to simply read and repeat words expressing a hand-related bodily action. Abstract verbs served as control. Changes in tremor kinematics were evaluated using a monoaxial accelerometer. Seventeen PD patients with rest tremor of the upper limbs were enrolled. Tremor amplitude was significantly smaller when reading action verbs as compared to abstract verbs. We provide empirical evidence supporting the embodied cognition theory by showing that circuits mediating tremor of PD patients are distinctively affected by processing action language.

Psychopathological constellation in patients with PNES: A new hypothesis.

Depression symptoms have often reported in patients with psychogenic nonepileptic seizures (PNES), although the underlying psychopathological symptomatology has been poorly understood. Our aim was to compare constellations of psychological and behavioral disturbance in PNES with respect to patients with mild-major depressive disorder (MDD), hypothesizing that the construct of depression might be different in the two groups. Ten patients with PNES and ten sex-/age-matched patients with mild-MDD newly-diagnosed, were enrolled in this study. A wide neuropsychiatric battery was employed including the following: symptoms checklist 90-R (SCL-90-R), Toronto alexithymia scale (TAS-20), Hamilton anxiety rating scale (HAMA), Beck depression inventory (BDI II), dissociative experiences scale (DES), traumatic experience checklist (TEC), somatoform dissociation questionnaire (SDQ-20), and temperament and character inventory-revised (TCI-R). No significant difference was detected in the large part of psychopathological examination including personality profile between the two groups. However, PNES showed high scores in alexithymia (p=0.02); anxiety (p=0.03), and somatoform symptomatology (p's<0.03) with respect to patients with mild-MDD. Moreover, somatoform symptoms strongly correlated with depression scores in both groups, whereas alexithymia was influenced by high anxiety level only in the group with PNES. No significant relationship was found between traumatic experience (as measured by TEC) and construct of depression. Our proof-of-concept study suggests that patients with PNES are characterized by their inability to verbalize emotions when dealing with anxiety symptoms, therefore expressing them in a somatic dimension. Further researches, including the investigation of the relationship between anxiety status and emotional expression, are warranted to better understand the pathogenesis of PNES.

The application of artificial intelligence to understand the pathophysiological basis of psychogenic nonepileptic seizures.

Psychogenic nonepileptic seizures (PNES) are episodes of paroxysmal impairment associated with a range of motor, sensory, and mental manifestations, which perfectly mimic epileptic seizures. Several patterns of neural abnormalities have been described without identifying a definite neurobiological substrate. In this multicenter cross-sectional study, we applied a multivariate classification algorithm on morphological brain imaging metrics to extract reliable biomarkers useful to distinguish patients from controls at an individual level. Twenty-three patients with PNES and 21 demographically matched healthy controls (HC) underwent an extensive neuropsychiatric/neuropsychological and neuroimaging assessment. One hundred and fifty morphological brain metrics were used for training a random forest (RF) machine-learning (ML) algorithm. A typical complex psychopathological construct was observed in PNES. Similarly, univariate neuroimaging analysis revealed widespread neuroanatomical changes affecting patients with PNES. Machine-learning approach, after feature selection, was able to perform an individual classification of PNES from controls with a mean accuracy of 74.5%, revealing that brain regions influencing classification accuracy were mainly localized within the limbic (posterior cingulate and insula) and motor inhibition systems (the right inferior frontal cortex (IFC)). This study provides Class II evidence that the considerable clinical and neurobiological heterogeneity observed in individuals with PNES might be overcome by ML algorithms trained on surface-based magnetic resonance imaging (MRI) data.

Advanced morphological neuroimaging study in lateral temporal lobe epilepsy: A multicentric study.

Lateral temporal lobe epilepsy (lTLE) is a rare condition characterized by auditory auras or receptive aphasia, negative MRI, and relatively benign evolution. With the low number of cases in the world, our objective was to analyze a cohort of sporadic cases with lTLE (slTLE), in order to investigate possible cerebral morphological alterations. Forty patients with lTLE (34.93±12.08years of age) and 38 healthy controls (CTRL, 34.55±9.08years of age) were enrolled from four tertiary Italian epilepsy centers, which provided brain MRI T1-weighted images following a standard protocol for patients with epilepsy. We performed group comparison by following different approaches: voxel-based morphometry (VBM, SPM8), cortical thickness (CT), and local gyrification index (lGI) (FreeSurfer 5.3). At a more conservative threshold (p<0.05, FWE correction), no significant differences between groups survived, neither in VBM nor CT/lGI. Multicenter studies have more power than smaller studies in conducting sophisticated evaluations of rare diseases, and further investigations are required to develop a full picture of this rare phenotype.

The movement time analyser task investigated with functional near infrared spectroscopy: an ecologic approach for measuring hemodynamic response in the motor system.

AIMS: Movement time analyzer (MTA) is an objective instrument to evaluate the degree of motor impairment as well as to investigate the dopaminergic drug effect in Parkinson's disease patients. The aim of this study is to validate a new ecologic neuroimaging tool for quantifying MTA-related hemodynamic response of the cortical motor system by means of functional near-infrared spectroscopy (fNIRS). MATERIALS: 11 right-handed healthy volunteers (six male and five female, age range 27-64 years) were studied with fNIRS and functional magnetic resonance imaging (fMRI) while performing MTA task for each hand. RESULTS: MTA performance was better for the dominant hand and younger participants. Both fNIRS and fMRI analyses revealed MTA-related increase of haemoglobin levels in the primary motor and premotor cortices contralateral to the moving hand. This response progressively increased with aging. CONCLUSION: These findings supported the translation of fNIRS-based MTA behavioural tool in clinical practice.

Magnetic resonance support vector machine discriminates between Parkinson disease and progressive supranuclear palsy.

BACKGROUND: The aim of the current study was to distinguish patients with Parkinson disease (PD) from those with progressive supranuclear palsy (PSP) at the individual level using pattern recognition of magnetic resonance imaging data. METHODS: We combined diffusion tensor imaging and voxel-based morphometry in a support vector machine algorithm to evaluate 21 patients with PSP and 57 patients with PD. RESULTS: The automated algorithm correctly distinguished patients who had PD from those who had PSP with 100% accuracy. This accuracy value was obtained when white matter atrophy was considered. Diffusion parameters combined with gray matter atrophy exhibited 90% sensitivity and 96% specificity. CONCLUSIONS: Our findings demonstrate that automated pattern recognition can help distinguish patients with PSP from those with PD on an individual basis.

Detection of hippocampal atrophy in patients with temporal lobe epilepsy: a 3-Tesla MRI shape.

In patients with mesial temporal lobe epilepsy (MTLE), brain MRI often detects hippocampal sclerosis (HS). Almost half of patients with MTLE do not show any hippocampal damage on visual or volumetric assessment. Here, we wished to prospectively assess 65 patients with MTLE (41 women, mean age: 39±10years, range: 21-69; right (12/65 patients) (MRI-negative) nMTLE; right (14/65 patients) (MRI-positive with HS) pMTLE; left (24/65 patients) nMTLE; and left (15/65 patients) pMTLE) using shape analysis (SA). There were significant differences among pMTLE versus nMTLE for age at seizure onset (20.2±12.8 vs. 31.8±16.7years; p=.0029), duration of epilepsy (14.6±12.7 vs. 21.3±9.6years; p=.0227), risk of refractoriness (p=.0067), frequency of antecedent febrile convulsions (FCs) (p<.001), as well as a history of epilepsy or FCs (p=.0104). All the subjects underwent the same 3-Tesla MRI protocol. Shape analysis of hippocampal formation was conducted comparing each group versus 44 matched controls. In all four subgroups, SA detected a significant atrophy in the corresponding hippocampus that coincided with the epileptogenic area. The damage was significantly more severe in patients with pMTLE (F value: 5.00) than in subgroups with nMTLE (F value: 3.50) and mainly corresponded to the CA1 subregion and subiculum. In the patients with MTLE, SA detects hippocampal damage that lateralizes with the epileptogenic area. Such damage is most prominent in the CA1 subregion and subiculum that are crucial in the pathogenesis of MTLE.

Hippocampal impairment in patients with Essential Tremor.

INTRODUCTION: There is growing evidence that a proportion of patients with Essential Tremor (ET) may develop a memory impairment over time. However, no studies have evaluated whether hippocampal damage really occur in ET. This study investigated the macro and micro-structural integrity of the hippocampus in ET subjects using a multimodal MRI approach. METHODS: Neuropsychological and MRI data were acquired from 110 participants (60 patients with ET and 50 age-, sex-, and education-matched healthy controls [HC]). Whole-brain T1-weighted and Diffusion Tensor Imaging (DTI) were performed to assess macro-and microstructural alterations. MRI parameters (volume; mean diffusivity [MD]; fractional anisotropy [FA]) of bilateral hippocampi were obtained. In order to evaluate the relationship between MRI alterations and neurocognitive impairment, hippocampal parameters were also correlated with cognitive test scores. RESULTS: Compared to controls, ET patients showed a subclinical memory impairment with significantly lower memory scores, but within the normal ranges. Despite the subclinical damage, however, ET patients showed a significant increase in MD values in the bilateral hippocampi in comparison with HC. A significant correlation was also found between MD and memory scores in ET. CONCLUSION: This study improves the knowledge on memory impairment in ET, as our results demonstrate for the first time the hippocampal microstructural damage related to subclinical memory impairment in ET patients. Further studies are needed before these findings can be considered predictive of a distinct ET subtype or suggestive of a co-occurent dementia.

A consensus guide to using functional near-infrared spectroscopy in posture and gait research.

BACKGROUND: Functional near-infrared spectroscopy (fNIRS) is increasingly used in the field of posture and gait to investigate patterns of cortical brain activation while people move freely. fNIRS methods, analysis and reporting of data vary greatly across studies which in turn can limit the replication of research, interpretation of findings and comparison across works. RESEARCH QUESTION AND METHODS: Considering these issues, we propose a set of practical recommendations for the conduct and reporting of fNIRS studies in posture and gait, acknowledging specific challenges related to clinical groups with posture and gait disorders. RESULTS: Our paper is organized around three main sections: 1) hardware set up and study protocols, 2) artefact removal and data processing and, 3) outcome measures, validity and reliability; it is supplemented with a detailed checklist. SIGNIFICANCE: This paper was written by a core group of members of the International Society for Posture and Gait Research and posture and gait researchers, all experienced in fNIRS research, with the intent of assisting the research community to lead innovative and impactful fNIRS studies in the field of posture and gait, whilst ensuring standardization of research.

Author Correction: The challenge of mapping the human connectome based on diffusion tractography.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

MRI Asymmetry Index of Hippocampal Subfields Increases Through the Continuum From the Mild Cognitive Impairment to the Alzheimer's Disease.

Objective: It is well-known that the hippocampus presents significant asymmetry in Alzheimer's disease (AD) and that difference in volumes between left and right exists and varies with disease progression. However, few works investigated whether the asymmetry degree of subfields of hippocampus changes through the continuum from Mild Cognitive Impairment (MCI) to AD. Thus, aim of the present work was to evaluate the Asymmetry Index (AI) of hippocampal substructures as possible MRI biomarkers of Dementia. Moreover, we aimed to assess whether the subfields presented peculiar differences between left and right hemispheres. We also investigated the relationship between the asymmetry magnitude in hippocampal subfields and the decline of verbal memory as assessed by Rey's auditory verbal learning test (RAVLT). Methods: Four-hundred subjects were selected from ADNI, equally divided into healthy controls (HC), AD, stable MCI (sMCI), and progressive MCI (pMCI). The structural baseline T1s were processed with FreeSurfer 6.0 and volumes of whole hippocampus (WH) and 12 subfields were extracted. The AI was calculated as: (|Left-Right|/(Left+Right))*100. ANCOVA was used for evaluating AI differences between diagnoses, while paired t-test was applied for assessing changes between left and right volumes, separately for each group. Partial correlation was performed for exploring relationship between RAVLT summary scores (Immediate, Learning, Forgetting, Percent Forgetting) and hippocampal substructures AI. The statistical threshold was Bonferroni corrected p < 0.05/13 = 0.0038. Results: We found a general trend of increased degree of asymmetry with increasing severity of diagnosis. Indeed, AD presented the higher magnitude of asymmetry compared with HC, sMCI and pMCI, in the WH (AI mean 5.13 ± 4.29 SD) and in each of its twelve subfields. Moreover, we found in AD a significant negative correlation (r = -0.33, p = 0.00065) between the AI of parasubiculum (mean 12.70 ± 9.59 SD) and the RAVLT Learning score (mean 1.70 ± 1.62 SD). Conclusions: Our findings showed that hippocampal subfields AI varies differently among the four groups HC, sMCI, pMCI, and AD. Moreover, we found-for the first time-that hippocampal substructures had different sub-patterns of lateralization compared with the whole hippocampus. Importantly, the severity in learning rate was correlated with pathological high degree of asymmetry in parasubiculum of AD patients.

Relationship between Hippocampal Subfields and Category Cued Recall in AD and PDD: A Multimodal MRI Study.

Alzheimer's disease (AD) and Parkinson's disease with dementia (PDD) are characterized by a different mnesic failure, particularly in memory cued recall. Although hippocampal involvement has been shown in both these diseases, it remains unknown whether a selective damage of specific subfields within the hippocampus may be responsible for the peculiar mnesic profile observed in AD and PDD. To explore this topic, we combined a multimodal 3 T-MRI hippocampal evaluation (whole-brain T1-weighted and diffusion tensor imaging) with a hippocampal-targeted neuropsychological assessment (Free and Cued Selective Reminding Test [FCSRT]) in 22 AD subjects, 18 PDD and 17 healthy controls. Macro- and microstructural features (volume; shape; mean diffusivity [MD]; fractional anisotropy [FA]) of bilateral hippocampi (whole and subfields) were obtained. Correlations between MRI-derived parameters and neuropsychological evaluations were performed. In the comparison between AD and PDD, the multimodal analysis allowed us to identify that subiculum, CA1 and CA4-DG were differently involved in these diseases and correlated with immediate and delayed total recall items of FCSRT. Moreover, compared to controls, AD showed a reduction in almost all subfields, with a MD increase in the same regions, whereas PDD displayed a volume loss, less severe than AD, more evident in the CA2-3 and presubiculum subfields. Our study provides new evidence that hippocampal subregions had different vulnerability to damage related to AD and PDD. The combination of the in vivo analysis of hippocampal subfields with the FCSRT paradigm provided important insights into whether changes within specific hippocampal subfields are related to the different mnesic profile in AD and PDD patients.

Near-Infrared Spectroscopy in Gait Disorders: Is It Time to Begin?

Walking is a complex motor behavior with a special relevance in clinical neurology. Many neurological diseases, such as Parkinson's disease and stroke, are characterized by gait disorders whose neurofunctional correlates are poorly investigated. Indeed, the analysis of real walking with the standard neuroimaging techniques poses strong challenges, and only a few studies on motor imagery or walking observation have been performed so far. Functional near-infrared spectroscopy (fNIRS) is becoming an important research tool to assess functional activity in neurological populations or for special tasks, such as walking, because it allows investigating brain hemodynamic activity in an ecological setting, without strong immobility constraints. A systematic review following PRISMA guidelines was conducted on the fNIRS-based examination of gait disorders. Twelve of the initial yield of 489 articles have been included in this review. The lesson learnt from these studies suggest that oxy-hemoglobin levels within the prefrontal and premotor cortices are more sensitive to compensation strategies reflecting postural control and restoration of gait disorders. Although this field of study is in its relative infancy, the evidence provided encourages the translation of fNIRS in clinical practice, as it offers a unique opportunity to explore in depth the activity of the cortical motor system during real walking in neurological patients. We also discuss to what extent fNIRS may be applied for assessing the effectiveness of rehabilitation programs.

Physiological Aging Influence on Brain Hemodynamic Activity during Task-Switching: A fNIRS Study.

Task-switching (TS) paradigm is a well-known validated tool useful for exploring the neural substrates of cognitive control, in particular the activity of the lateral and medial prefrontal cortex. This work is aimed at investigating how physiological aging influences hemodynamic response during the execution of a color-shape TS paradigm. A multi-channel near infrared spectroscopy (fNIRS) was used to measure hemodynamic activity in 27 young (30.00 ± 7.90 years) and 11 elderly participants (57.18 ± 9.29 years) healthy volunteers (55% male, age range: (19-69) years) during the execution of a TS paradigm. Two holders were placed symmetrically over the left/right hemispheres to record cortical activity [oxy-(HbO) and deoxy-hemoglobin (HbR) concentration] of the dorso-lateral prefrontal cortex (DLPFC), the dorsal premotor cortex (PMC), and the dorso-medial part of the superior frontal gyrus (sFG). TS paradigm requires participants to repeat the same task over a variable number of trials, and then to switch to a different task during the trial sequence. A two-sample t-test was carried out to detect differences in cortical responses between groups. Multiple linear regression analysis was used to evaluate the impact of age on the prefrontal neural activity. Elderly participants were significantly slower than young participants in both color- (p < 0.01, t = -3.67) and shape-single tasks (p = 0.026, t = -2.54) as well as switching (p = 0.026, t = -2.41) and repetition trials (p = 0.012, t = -2.80). Differences in cortical activation between groups were revealed for HbO mean concentration of switching task in the PMC (p = 0.048, t = 2.94). In the whole group, significant increases of behavioral performance were detected in switching trials, which positively correlated with aging. Multivariate regression analysis revealed that the HbO mean concentration of switching task in the PMC (p = 0.01, ß = -0.321) and of shape single-task in the sFG (p = 0.003, ß = 0.342) were the best predictors of age effects. Our findings demonstrated that TS might be a reliable instrument to gather a measure of cognitive resources in older people. Moreover, the fNIRS-related brain activity extracted from frontoparietal cortex might become a useful indicator of aging effects.

The challenge of mapping the human connectome based on diffusion tractography.

Tractography based on non-invasive diffusion imaging is central to the study of human brain connectivity. To date, the approach has not been systematically validated in ground truth studies. Based on a simulated human brain data set with ground truth tracts, we organized an open international tractography challenge, which resulted in 96 distinct submissions from 20 research groups. Here, we report the encouraging finding that most state-of-the-art algorithms produce tractograms containing 90% of the ground truth bundles (to at least some extent). However, the same tractograms contain many more invalid than valid bundles, and half of these invalid bundles occur systematically across research groups. Taken together, our results demonstrate and confirm fundamental ambiguities inherent in tract reconstruction based on orientation information alone, which need to be considered when interpreting tractography and connectivity results. Our approach provides a novel framework for estimating reliability of tractography and encourages innovation to address its current limitations.

Hippocampal Subfield Atrophies in Converted and Not-Converted Mild Cognitive Impairments Patients by a Markov Random Fields Algorithm.

Although measurement of total hippocampal volume is considered as an important hallmark of Alzheimer's disease (AD), recent evidence demonstrated that atrophies of hippocampal subregions might be more sensitive in predicting this neurodegenerative disease. The vast majority of neuroimaging papers investigating this topic are focused on the difference between AD and patients with mild cognitive impairment (MCI), not considering the impact of MCI patients who will or not convert in AD. For this reason, the aim of this study was to determine if measurements of hippocampal subfields provide advantages over total hippocampal volume for discriminating these groups. Hippocampal subfields volumetry was extracted in 55 AD, 32 converted and 89 not-converted MCI (c/nc-MCI) and 47 healthy controls, using an atlas-based automatic algorithm based on Markov random fields embedded in the Freesurfer framework. To evaluate the impact of hippocampal atrophy in discriminating the insurgence of AD-like phenotypes we used three classification methods: Support Vector Machine, Naïve Bayesian Classifier and Neural Networks Classifier. Taking into account only the total hippocampal volume, all classification models, reached a sensitivity of about 66% in discriminating between c-MCI and nc-MCI. Otherwise, classification analysis considering all segmenting subfields increased accuracy to diagnose c-MCI from 68% to 72%. This effect resulted to be strongly dependent upon atrophies of the subiculum and presubiculum. Our multivariate analysis revealed that the magnitude of the difference considering hippocampal subfield volumetry, as segmented by the considered atlas-based automatic algorithm, offers an advantage over hippocampal volume in distinguishing early AD from nc-MCI.