Metaplasticity A Promising Tool to Disentangle Chronic Disorders of Consciousness Differential Diagnosis

The extent of cortical reorganization after brain injury in patients with Vegetative State/Unresponsive Wakefulness Syndrome (UWS) and Minimally Conscious State (MCS) depends on the residual capability of modulating synaptic plasticity. Neuroplasticity is largely abnormal in patients with UWS, although the fragments of cortical activity may exist, while patients MCS show a better cortical organization. The aim of this study was to evaluate cortical excitability in patients with disorders of consciousness (DoC) using a transcranial direct current stimulation (TDCS) metaplasticity protocol. To this end, we tested motor-evoked potential (MEP) amplitude, short intracortical inhibition (SICI), and intracortical facilitation (ICF). These measures were correlated with the level of consciousness (by the Coma Recovery Scale-Revised, CRS-R). MEP amplitude, SICI, and ICF strength were significantly modulated following different metaplasticity TDCS protocols only in the patients with MCS. SICI modulations showed a significant correlation with the CRS-R score. Our findings demonstrate, for the first time, a partial preservation of metaplasticity properties in some patients with DoC, which correlates with the level of awareness. Thus, metaplasticity assessment may help the clinician in differentiating the patients with DoC, besides the clinical evaluation. Moreover, the responsiveness to metaplasticity protocols may identify the subjects who could benefit from neuromodulation protocols

Motor recovery after stroke: the role of overground exoskeletons in shaping brain plasticity

The use of neurorobotic devices into gait rehabilitative programs, including Ekso, is reported to increase the engagement and motivation of the patients while actively performing a task, and to shape the sensory-motor plasticity (SMP) and its balance between the primary motor areas (M1), and the fronto-parietal network (FPN) connectivity, thus contributing to successful gait rehabilitation [1]. Aim of our study was to assess whether Ekso would foster the recovery of deteriorated FPN connectivity and SMP patterns involved in limb coordination during walking [2] in a sample of patients with hemiparesis due to stroke. To this end, we enrolled ten patients who underwent Ekso training (24 sessions) and were evaluated about gait performance, FPN connectivity, and SMP pattern. Esko significantly increased gait performance index as revealed by surface EMG (p=0.01) and the deterioration of prefrontal-SMA and SMA-centroparietal connectivity (both p=0.02), and rebalanced the equilibrium between the SMP patterns of the two M1-leg areas (p=0.03). Moreover, the baseline plasticity and FPN connectivity were the most important factors in using Ekso fruitfully (r=0.9, p=0.03). Even though our findings need to be confirmed by future research further addressing the safety and effectively use of Ekso, our small cohort study provides new cues supporting the role of powered exoskeletons in rehabilitation protocols for persons with stroke

The role of virtual reality in improving gait abnormalities

To regain walking after a neurological disorder is considered one of the primary goals of the rehabilitation process, given that gait abnormalities are often disabling, negatively impacting patients’ quality of life. In the last years there has been an intense technological development of robotic devices to overcome such problems. The robotic rehabilitation tools are typically based on the so-called phenomenon of motor learning, resulting from intensive, repetitive, and task-oriented motor activities that require patient’s effort and attention [1]. Such robotic devices can be classified into stationary and overground walking systems: stationary systems (treadmill gait trainers such as Lokomat, and programmable foot end-effector trainers including Geo-System) and overground walking systems (e.g. Ekso-GT). Stationary devices and new treadmill and balance platforms, such as C-Mill and CAREN, may be equipped with virtual reality, to further improve functional outcomes. Virtual reality is conceived to put the patient in a situation to generate the augmented feedback towards his central nervous system (augmented feedback) through exercises performed in a virtual environment which help to develop knowledge of results of the movements (knowledge of results) and knowledge of the quality of the movements (knowledge of performance). Thanks to this, the central nervous system can activate a physiological key learning mechanism called “reinforcement learning” which implies an increase of the specific information of a movement to produce an effective improvement of performance quality

Update on intensive motor training in spinocerebellar ataxia: time to move a step forward?:

Some evidence suggests that high-intensity motor training slows down the severity of spinocerebellar ataxia. However, whether all patients might benefit from these activities, and by which activity, and the underlying mechanisms remain unclear. We provide an update on the effect and limitations of different training programmes in patients with spinocerebellar ataxias. Overall, data converge of the finding that intensive training is still based either on conventional rehabilitation protocols or whole-body controlled videogames ("exergames"). Notwithstanding the limitations, short-term improvement is observed, which tends to be lost once the training is stopped. Exergames and virtual reality can ameliorate balance, coordination, and walking abilities, whereas the efficacy of adapted physical activity, gym, and postural exercises depends on the disease duration and severity. In conclusion, although a disease-modifying effect has not been demonstrated, constant, individually tailored, high-intensity motor training might be effective in patients with degenerative ataxia, even in those with severe disease. These approaches may enhance the remaining cerebellar circuitries or plastically induce compensatory networks. Further research is required to identify predictors of training success, such as the type and severity of ataxia and the level of residual functioning

Combining EEG signal processing with supervised methods for Alzheimer’s patients classification

Background Alzheimer’s Disease (AD) is a neurodegenaritive disorder characterized by a progressive dementia, for which actually no cure is known. An early detection of patients affected by AD can be obtained by analyzing their electroencephalography (EEG) signals, which show a reduction of the complexity, a perturbation of the synchrony, and a slowing down of the rhythms. Methods In this work, we apply a procedure that exploits feature extraction and classification techniques to EEG signals, whose aim is to distinguish patient affected by AD from the ones affected by Mild Cognitive Impairment (MCI) and healthy control (HC) samples. Specifically, we perform a time-frequency analysis by applying both the Fourier and Wavelet Transforms on 109 samples belonging to AD, MCI, and HC classes. The classification procedure is designed with the following steps: (i) preprocessing of EEG signals; (ii) feature extraction by means of the Discrete Fourier and Wavelet Transforms; and (iii) classification with tree-based supervised methods. Results By applying our procedure, we are able to extract reliable human-interpretable classification models that allow to automatically assign the patients into their belonging class. In particular, by exploiting a Wavelet feature extraction we achieve 83%, 92%, and 79% of accuracy when dealing with HC vs AD, HC vs MCI, and MCI vs AD classification problems, respectively. Conclusions Finally, by comparing the classification performances with both feature extraction methods, we find out that Wavelets analysis outperforms Fourier. Hence, we suggest it in combination with supervised methods for automatic patients classification based on their EEG signals for aiding the medical diagnosis of dementia

Impaired Cerebral Haemodynamics in Vascular Depression: Insights From Transcranial Doppler Ultrasonography

Introduction: Late-life depression is a well-known risk factor for future dementia. Increasing evidences also show a link between cerebral hypoperfusion and neurodegeneration, although data on Transcranial Doppler ultrasonography (TCD)-derived measures in patients with “Vascular Depression” (VD) are lacking. The aim of this study was to assess and correlate TCD parameters with cognitive function and severity of subcortical ischemic vascular disease in a sample of VD patients.Methods: Seventy six patients (mean age 72.5 ± 5.3 years; 53.9% females) met the DSM-5 diagnostic criteria for unipolar major depression. Mean blood flow velocity (MBFv) and pulsatility index (PI) were recorded from the middle cerebral artery. Quantification of depressive symptoms (17-item Hamilton Depression Rating Scale –HDRS), neuropsychological test evaluating frontal lobe abilities (Stroop Color-Word test interference—Stroop T), and white matter lesions (WMLs) load according to the Fazekas visual score were also assessed.Results: WMLs severity was mild in 20 patients (group I), moderate in 32 (group II), and severe in 24 (group III). The groups were comparable in terms of clinical features, vascular risk factors profile, and HDRS score, whereas Stroop T score was worse in group III. An increased PI and a reduced MBFv were found in VD patients with severe WMLs. According to the regression analysis, a reduced MBFv was independently and significantly associated with depressive symptoms and executive dysfunction, even after adjusting for demographic features and vascular risk factors. Similarly, an independent and significant association was observed between the increase of PI and both Stroop T and WMLs severity.Conclusions: A TCD profile of low perfusion and high vascular resistance in VD patients suggests a diffuse cerebrovascular pathology likely arising from the small vessels and then extending to larger arteries. Hemodynamic dysfunction might play a pathogenic role in the development of cognitive impairment in patients with late-life depression and subcortical ischemic vascular disease. TCD represents a valuable tool in the early detection, assessment, and management of VD patients at risk for dementia

Red nucleus structure and function: from anatomy to clinical neurosciences

The red nucleus (RN) is a large subcortical structure located in the ventral midbrain. Although it originated as a primitive relay between the cerebellum and the spinal cord, during its phylogenesis the RN shows a progressive segregation between a magnocellular part, involved in the rubrospinal system, and a parvocellular part, involved in the olivocerebellar system. Despite exhibiting distinct evolutionary trajectories, these two regions are strictly tied together and play a prominent role in motor and non-motor behavior in different animal species. However, little is known about their function in the human brain. This lack of knowledge may have been conditioned both by the notable differences between human and non-human RN and by inherent difficulties in studying this structure directly in the human brain, leading to a general decrease of interest in the last decades. In the present review, we identify the crucial issues in the current knowledge and summarize the results of several decades of research about the RN, ranging from animal models to human diseases. Connecting the dots between morphology, experimental physiology and neuroimaging, we try to draw a comprehensive overview on RN functional anatomy and bridge the gap between basic and translational research

Naturally occurring compounds in differentiation based therapy of cancer.

Differentiation of cancer cells entails the reversion of phenotype from malignant to the original. The conversion to cell type characteristic for another tissue is named transdifferentiation. Differentiation/transdifferentiation of malignant cells in high grade tumor mass could serve as a nonaggressive approach that potentially limits tumor progression and augments chemosensitivity. While this therapeutic strategy is already being used for treatment of hematological cancers, its feasibility for solid malignancies is still debated. We will presently discuss the natural compounds that show these properties, with focus on anthraquinones from Aloe vera, Senna, Rheum sp. and hop derived prenylflavonoids

In vivo probabilistic atlas of white matter tracts of the human subthalamic area combining track density imaging and optimized diffusion tractography

The human subthalamic area is a region of high anatomical complexity, tightly packed with tiny fiber bundles. Some of them, including the pallidothalamic, cerebello-thalamic, and mammillothalamic tracts, are relevant targets in functional neurosurgery for various brain diseases. Diffusion-weighted imaging-based tractography has been suggested as a useful tool to map white matter pathways in the human brain in vivo and non-invasively, though the reconstruction of these specific fiber bundles is challenging due to their small dimensions and complex anatomy. To the best of our knowledge, a population-based, in vivo probabilistic atlas of subthalamic white matter tracts is still missing. In the present work, we devised an optimized tractography protocol for reproducible reconstruction of the tracts of subthalamic area in a large data sample from the Human Connectome Project repository. First, we leveraged the super-resolution properties and high anatomical detail provided by short tracks track-density imaging (stTDI) to identify the white matter bundles of the subthalamic area on a group-level template. Tracts identification on the stTDI template was also aided by visualization of histological sections of human specimens. Then, we employed this anatomical information to drive tractography at the subject-level, optimizing tracking parameters to maximize between-subject and within-subject similarities as well as anatomical accuracy. Finally, we gathered subject level tracts reconstructed with optimized tractography into a large-scale, normative population atlas. We suggest that this atlas could be useful in both clinical anatomy and functional neurosurgery settings, to improve our understanding of the complex morphology of this important brain region