ECG Approximate Entropy in the Elderly during Cycling Exercise.

Approximate entropy (ApEn) is used as a nonlinear measure of heart-rate variability (HRV) in the analysis of ECG time-series recordings. Previous studies have reported that HRV can differentiate between frail and pre-frail people. In this study, EEGs and ECGs were recorded from 38 elderly adults while performing a three-stage cycling routine. Before and after cycling stages, 5-min resting-state EEGs (rs-EEGs) and ECGs were also recorded under the eyes-open condition. Applying the K-mean classifier to pre-exercise rs-ECG ApEn values and body weights revealed nine females with EEG power which was far higher than that of the other subjects in all cycling stages. The breathing of those females was more rapid than that of other subjects and their average heart rate was faster. Those females also presented higher degrees of asymmetry in the alpha and theta bands (stronger power levels in the right frontal electrode), indicating stressful responses during the experiment. It appears that EEG delta activity could be used in conjunction with a very low ECG frequency power as a predictor of bursts in the heart rate to facilitate the monitoring of elderly adults at risk of heart failure. A resting ECG ApEn index in conjunction with the subject's weight or BMI is recommended for screening high-risk candidates prior to exercise interventions.

Application of Convolutional Neural Network for Fingerprint-Based Prediction of Gender, Finger Position, and Height.

Fingerprints are the most common personal identification feature and key evidence for crime scene investigators. The prediction of fingerprints features include gender, height range (tall or short), left or right hand, and finger position can effectively narrow down the list of suspects, increase the speed of comparison, and greatly improve the effectiveness of criminal investigations. In this study, we used three commonly used CNNs (VGG16, Inception-v3, and Resnet50) to perform biometric prediction on 1000 samples, and the results showed that VGG16 achieved the highest accuracy in identifying gender (79.2%), left- and right-hand fingerprints (94.4%), finger position (84.8%), and height range (69.8%, using the ring finger of male participants). In addition, we visualized the CNN classification basis by the Grad-CAM technique and compared the results with those predicted by experts and found that the CNN model outperformed experts in terms of classification accuracy and speed, and provided good reference for fingerprints that were difficult to determine manually.

Differences in Physiological Signals Due to Age and Exercise Habits of Subjects during Cycling Exercise.

Numerous studies indicated the physical benefits of regular exercise, but the neurophysiological mechanisms of regular exercise in elders were less investigated. We aimed to compare changes in brain activity during exercise in elderly people and in young adults with and without regular exercise habits. A total of 36 healthy young adults (M/F:18/18) and 35 healthy elderly adults (M/F:20/15) participated in this study. According to exercise habits, each age group were classified into regular and occasional exerciser groups. ECG, EEG, and EMG signals were recorded using V-AMP with a 1-kHz sampling rate. The participants were instructed to perform three 5-min bicycle rides with different exercise loads. The EEG spectral power of elders who exercised regularly revealed the strongest positive correlation with their exercise intensity by using Pearson correlation analysis. The results demonstrate that exercise-induced significant cortical activation in the elderly participants who exercised regularly, and most of the p-values are less than 0.001. No significant correlation was observed between spectral power and exercise intensity in the elders who exercised occasionally. The young participants who exercised regularly had greater cardiac and neurobiological efficiency. Our results may provide a new exercise therapy reference for adult groups with different exercise habits, especially for the elders.

Alteration of the Intra- and Inter-Lobe Connectivity of the Brain Structural Network in Normal Aging.

The morphological changes in cortical parcellated regions during aging and whether these atrophies may cause brain structural network intra- and inter-lobe connectivity alterations are subjects that have been minimally explored. In this study, a novel fractal dimension-based structural network was proposed to measure atrophy of 68 parcellated cortical regions. Alterations of structural network parameters, including intra- and inter-lobe connectivity, were detected in a middle-aged group (30-45 years old) and an elderly group (50-65 years old). The elderly group exhibited significant lateralized atrophy in the left hemisphere, and most of these fractal dimension atrophied regions were included in the regions of the "last-in, first-out" model. Globally, the elderly group had lower modularity values, smaller component size modules, and fewer bilateral association fibers. They had lower intra-lobe connectivity in the frontal and parietal lobes, but higher intra-lobe connectivity in the temporal and occipital lobes. Both groups exhibited similar inter-lobe connecting pattern. The elderly group revealed separations, sparser long association fibers, commissural fibers, and lateral inter-lobe connectivity lost effect, mainly in the right hemisphere. New wiring and reconfiguring modules may have occurred within the brain structural network to compensate for connectivity, decreasing and preventing functional loss in cerebral intra- and inter-lobe connectivity.

Intra- and Inter-Modular Connectivity Alterations in the Brain Structural Network of Spinocerebellar Ataxia Type 3.

In addition to cerebellar degeneration symptoms, patients with spinocerebellar ataxia type 3 (SCA3) exhibit extensive involvements with damage in the prefrontal cortex. A network model has been proposed for investigating the structural organization and functional mechanisms of clinical brain disorders. For neural degenerative diseases, a cortical feature-based structural connectivity network can locate cortical atrophied regions and indicate how their connectivity and functions may change. The brain network of SCA3 has been minimally explored. In this study, we investigated this network by enrolling 48 patients with SCA3 and 48 healthy subjects. A novel three-dimensional fractal dimension-based network was proposed to detect differences in network parameters between the groups. Copula correlations and modular analysis were then employed to categorize and construct the structural networks. Patients with SCA3 exhibited significant lateralized atrophy in the left supratentorial regions and significantly lower modularity values. Their cerebellar regions were dissociated from higher-level brain networks, and demonstrated decreased intra-modular connectivity in all lobes, but increased inter-modular connectivity in the frontal and parietal lobes. Our results suggest that the brain networks of patients with SCA3 may be reorganized in these regions, with the introduction of certain compensatory mechanisms in the cerebral cortex to minimize their cognitive impairment syndrome.

Disrupted cerebellar connectivity reduces whole-brain network efficiency in multiple system atrophy.

Multiple system atrophy of the cerebellar type is a sporadic neurodegenerative disorder of the central nervous system. We hypothesized that the white matter degeneration of the cerebellum and pons in this disease may cause a breakdown of cerebellar structural networks and further reduce the network efficiency of cerebellar-connected cerebral regions. Diffusion tensor tractography was used to construct the structural networks of 19 cerebellar-type multiple system atrophy patients, who were compared with 19 age- and sex-matched controls. Graph theory was used to assess the small-world properties and topological organization of structure networks in both the control and patient groups. Our results showed that the cerebellar-type multiple system atrophy patients exhibited altered small-world architecture with significantly increased characteristic shortest path lengths and decreased clustering coefficients. We also found that white matter degeneration in the cerebellum was characterized by reductions in network strength (number and integrity of fiber connections) of the cerebellar regions, which further induced extensively decreased network efficiency for numerous cerebral regions. Finally, we found that the reductions in nodal efficiency of the cerebellar lobules and bilateral sensorimotor, prefrontal, and basal ganglia regions negatively correlated with the severity of ataxia for the cerebellar-type multiple system atrophy patients. This study demonstrates for the first time that the brains of cerebellar-type multiple system atrophy patients exhibit disrupted topological organization of white matter structural networks. Thus, this study provides structural evidence of the relationship between abnormalities of white matter integrity and network efficiency that occurs in cerebellar-type multiple system atrophy.

Gait performance and prefrontal cortex activation during single and dual task walking in older adults with different cognitive levels.

Background: Growing evidence shows the cognitive function influences the motor performance. The prefrontal cortex (PFC) as a part of the executive locomotor pathway is also important for cognitive function. This study investigated the differences in motor function and brain activity among older adults with different cognitive levels, and examined the significance of cognition on motor functions. Methods: Normal control (NC), individuals with mild cognitive impairment (MCI) or mild dementia (MD) were enrolled in this study. All participants received a comprehensive assessment including cognitive function, motor function, PFC activity during walking, and fear of fall. The assessment of cognitive function included general cognition, attention, executive function, memory, and visuo-spatial. The assessment of motor function included timed up and go (TUG) test, single walking (SW), and cognitive dual task walking (CDW). Results: Individuals with MD had worse SW, CDW and TUG performance as compared to individuals with MCI and NC. These gait and balance performance did not differ significantly between MCI and NC. Motor functions all correlated with general cognition, attention, executive function, memory, and visuo-spatial ability. Attention ability measured by trail making test A (TMT-A) was the best predictor for TUG and gait velocity. There were no significant differences in PFC activity among three groups. Nevertheless, the PFC activated more during CDW as compared with SW in individuals with MCI (p = 0.000), which was not demonstrated in the other two groups. Conclusion: MD demonstrated worse motor function as compared to NC and MCI. The greater PFC activity during CDW in MCI may be considered as a compensatory strategy for maintaining the gait performance. Motor function was related to the cognitive function, and the TMT A was the best predictor for the gait related performance in present study among older adults.

Quantifying cerebellar atrophy in multiple system atrophy of the cerebellar type (MSA-C) using three-dimensional gyrification index analysis.

Multiple system atrophy of the cerebellar type (MSA-C) is a degenerative neurological disease of the central nervous system. This study employed a method named, "surface-based three-dimensional gyrification index" (3D-GI) to quantify morphological changes in normal cerebellum (including brainstem) and atrophied cerebellum, in patients with MSA-C. We assessed whether 3D-GI can exclude gender and age differences to quantify cerebellum and brainstem atrophy more accurately. Sixteen healthy subjects and 16 MSA-C patients participated in this study. We compared 3D-GI values and volumes in the cerebellum, based on T1-weighted MR images. We also compared the images of reconstructed 3D cerebellum gray matter (3D-CBGM) and cerebellum white matter (3D-CBWM) to detect the atrophied cerebellar region in MSA-C patients. The 3D-GI values were in a stable range with small variances, exhibiting no gender effect and no age-related shrinkage. Significantly lower 3D-GI values were exhibited in both CBGM and CBWM of the MSA-C patients compared with healthy subjects, even in the early phases of the disease. Decreases in 3D-GI values indicated the degeneration of the cerebellar folding structure, exactly reflecting the morphological changes in cerebellum. The 3D-GI method based on CBGM resulted in superior discriminative accuracy compared with the CBGM volumetric method. Using the two-dimensional 3D-GI values, the K-means classifier can evidently discriminate the MSA-C patients from healthy subjects.

Comparison of cerebellar ataxias: A three-year prospective longitudinal assessment.

We quantitatively investigated the clinical severity and progression of diseases with ataxia, as measured with the Scale for the Assessment and Rating of Ataxia, and examined the potential application of the Scale for the Assessment and Rating of Ataxia for future therapeutic trials. Severity of ataxia was assessed in 238 patients with spinocerebellar ataxia type 2, spinocerebellar ataxia type 3, spinocerebellar ataxia type 6, spinocerebellar ataxia type 17, multiple system atrophy-cerebellar variant, or Gerstman-Sträussler-Scheinker disease. Among them, 119 (50%) were longitudinally examined three to seven times, in a period of 8 to 38 months, resulting in a total set of 535 assessments. The differences between spinocerebellar ataxia and multiple system atrophy-cerebellar variant were ascertained cross-sectionally and longitudinally. Gerstman-Sträussler-Scheinker disease had the fastest progression, followed by multiple system atrophy-cerebellar variant, spinocerebellar ataxia type 17, spinocerebellar ataxia type 3, spinocerebellar ataxia type 2, and spinocerebellar ataxia type 6. Patients with multiple system atrophy-cerebellar variant had a faster progression in gait, sitting, speech, and total score than patients with spinocerebellar ataxias. For a randomized, case-control trial, a sample size of 47 for spinocerebellar ataxia and 85 for multiple system atrophy-cerebellar variant in the treatment or placebo arms would have a sufficient statistical power to demonstrate the efficacy of a new therapy that would retard ataxia progression by 1 point per year as measured by the Scale for the Assessment and Rating of Ataxia. The results will have a significant impact on the planning and implementation of future therapeutic trials of spinocerebellar ataxia and multiple system atrophy-cerebellar variant.

Use of diffusion tensor imaging to identify similarities and differences between cerebellar and Parkinsonism forms of multiple system atrophy.

INTRODUCTION: We performed diffusion tensor imaging to determine if multiple system atrophy (MSA)-cerebellar (C) and MSA-Parkinsonism (P) show similar changes, as shown in pathological studies. METHODS: Nineteen patients with MSA-C, 12 patients with MSA-P, 20 patients with Parkinson disease, and 20 healthy controls were evaluated with the use of voxel-based morphometry analysis of diffusion tensor imaging. RESULTS: There was an increase in apparent diffusion coefficient values in the middle cerebellar peduncles and cerebellum and a decrease in fractional anisotropy in the pyramidal tract, middle cerebellar peduncles, and white matter of the cerebellum in patients with MSA-C and MSA-P compared to the controls (P < 0.001). In addition, isotropic diffusion-weighted image values were reduced in the cerebellar cortex and deep cerebellar nuclei in patients with MSA-C and increased in the basal ganglia in patients with MSA-P. CONCLUSION: These results indicate that despite their disparate clinical manifestations, patients with MSA-C and MSA-P share similar diffusion tensor imaging features in the infratentorial region. Further, the combination of FA, ADC and iDWI images can be used to distinguish between MSA (either form) and Parkinson disease, which has potential therapeutic implications.

Fractal dimension analysis for quantifying cerebellar morphological change of multiple system atrophy of the cerebellar type (MSA-C).

Multiple system atrophy of the cerebellar type (MSA-C) is a degenerative neurological disease of the central nervous system. This study aims to demonstrate that the morphological changes of cerebellar structure, specifically, the cerebellum white matter (CBWM) and cerebellum gray matter (CBGM) from T1-weighted magnetic resonance (MR) images, can be quantified by three-dimensional (3D) fractal dimension (FD) analysis, which is a measure of complexity. Twenty-three MSA-C patients and twenty-one normal subjects participated in this study. The results of this study show that MSA-C patients presented significantly lower FD values compared to the control group, and that morphological change in the CBWM dominates the cerebellar degeneration. In addition, the FD analysis method is superior to conventional volumetric methods in quantifying the structural changes of WM and GM because it exhibits smaller variances and less gender effect. Since a decrease of cerebellar FD value indicates degeneration of the cerebellar structure, this study further suggests that the morphological changes of cerebellar structures (CBGM and CBWM) can be characterized by FD analysis.

Supratentorial and Infratentorial Lesions in Spinocerebellar Ataxia Type 3.

Background: Spinocerebellar ataxia type 3 (SCA) is a cerebellum-dominant degenerative disorder that is characterized primarily by infratentorial damage, although less severe supratentorial involvement may contribute to the clinical manifestation. These impairments may result from the efferent loss of the cerebellar cortex and degeneration of the cerebral cortex. Method: We used the three-dimensional fractal dimension (3D-FD) method to quantify the morphological changes in the supratentorial regions and assessed atrophy in the relatively focal regions in patients with SCA3. A total of 48 patients with SCA3 and 50 sex- and age-matched healthy individuals, as the control group, participated in this study. The 3D-FD method was proposed to distinguish 97 automatic anatomical label regions of gray matter (left cerebrum: 45, right cerebrum: 45, cerebellum: 7) between healthy individuals and patients with SCA3. Results: Patients with SCA3 exhibited reduced brain complexity within both the traditional olivopontocerebellar atrophy (OPCA) pattern and specific supratentorial regions. The study results confirmed the extensive involvement of extracerebellar regions in SCA3. The atrophied regions of SCA3 in infratentorial and supratentorial cortex showed a wide range of overlapped areas as in two functional cortexes, namely cerebellum-related cortex and basal ganglia-related cortex. Conclusions: Our results found that the atrophy of the SCA3 are not only limited in the infratentorial regions. Both cerebellar related cortex and basal ganglia related cortex were affected in the disease process of SCA3. Our findings might correlate to the common symptoms of SCA3, such as ataxia, Parkinsonism, dysarthria, and dysmetria. SCA3 should no longer be considered a disease limited to the cerebellum and its connections; rather, it should be considered a pathology affecting the whole brain.

Combining analysis of multi-parametric MR images into a convolutional neural network: Precise target delineation for vestibular schwannoma treatment planning.

Manual delineation of vestibular schwannoma (VS) by magnetic resonance (MR) imaging is required for diagnosis, radiosurgery dose planning, and follow-up tumor volume measurement. A rapid and objective automatic segmentation method is required, but problems have been encountered due to the low through-plane resolution of standard VS MR scan protocols and because some patients have non-homogeneous cystic areas within their tumors. In this study, we retrospectively collected multi-parametric MR images from 516 patients with VS; these were extracted from the Gamma Knife radiosurgery planning system and consisted of T1-weighted (T1W), T2-weighted (T2W), and T1W with contrast (T1W + C) images. We developed an end-to-end deep-learning-based method via an automatic preprocessing pipeline. A two-pathway U-Net model involving two sizes of convolution kernel (i.e., 3 × 3 × 1 and 1 × 1 × 3) was used to extract the in-plane and through-plane features of the anisotropic MR images. A single-pathway model that adopted the same architecture as the two-pathway model, but used a kernel size of 3 × 3 × 3, was also developed for comparison purposes. In addition, we used multi-parametric MR images with different image contrasts as the model training input in order to effectively segment tumors with solid as well as cystic parts. The results of the automatic segmentation demonstrated that (1) the two-pathway model outperformed single-pathway model in terms of dice scores (0.90 ± 0.05 versus 0.87 ± 0.07); both of them having been trained using the T1W, T1W + C and T2W anisotropic MR images, (2) the optimal single-parametric two-pathway model (dice score: 0.88 ± 0.06) was then trained using the T1W + C images, and (3) the two-pathway models trained using bi-parametric (T1W + C and T2W) and tri-parametric (T1W, T2W, and T1W + C) images outperformed the model trained using the single-parametric (T1W + C) images (dice scores: 0.89 ± 0.05 and 0.90 ± 0.05, respectively, larger than 0.88 ± 0.06) because it showed improved segmentation of the non-homogeneous parts of the tumors. The proposed two-pathway U-Net model outperformed the single-pathway U-Net model when segmenting VS using anisotropic MR images. The multi-parametric models effectively improved on the defective segmentation obtained using the single-parametric models by separating the non-homogeneous tumors into their solid and cystic parts.

Morphological regionalization using fetal magnetic resonance images of normal developing brains.

Regional differences in human brain development during infancy have been studied for many years, but little is known about how regionalization of the brain proceeds during intrauterine life. We investigated the regionalization of cerebral volume and cortical convolutions based on the volumetric magnetic resonance images (MRIs) of 43 fetuses, ranging from 21 to 37 weeks of gestation. Two plausible parcellations of MRI are proposed, and curvature index together with gyrification index are used to quantify the regional cortical convolutions. Our results elucidate that the cortical foldings among different brain regions develop at comparable rates, suggesting a similar uniformity of changes in size of the cortical sheet in these regions over time. On the contrary, the growth of the cerebral volume presents regional difference, with the frontal and parieto-temporal regions growing significantly faster than other regions due to the contribution from expansion of basal ganglia. This quantitative regional information suggests that cerebral volume is not a relevant parameter to measure in relation to gyrification, and that the size of the cortical sheet is more likely to be directly related to cortical folding. The availability of quantitative regional information on normal fetal brains in utero will allow clinical application of this information when probing neurodevelopmental disorders in the future.

Genetic Predisposition and Disease Expression of Bipolar Disorder Reflected in Shape Changes of the Anterior Limbic Network.

Bipolar disorder (BD) is a genetically and phenotypically complex psychiatric disease. Although previous studies have suggested that the relatives of BD patients have an increased risk of experiencing affective disturbances, most relatives who have similar genotypes may not manifest the disorder. We aim to identify the neuroimaging alterations-specifically, the cortical folding structures of the anterior limbic network (ALN)-in BD patients and their siblings, compared to healthy controls. The shared alterations in patients and their siblings may indicate the hereditary predisposition of BD, and the altered cortical structures unique to BD patients may be a probe of BD expression. High-resolution, T1-weighted magnetic resonance images for 17 euthymic patients with BD, 17 unaffected siblings of BD patients, and 22 healthy controls were acquired. We categorized the cortical regions within the ALN into sulcal and gyral areas, based on the shape index, followed by the measurement of the folding degree, using the curvedness. Our results revealed that the changes in cortical folding in the orbitofrontal and temporal regions were associated with a hereditary predisposition to BD. Cortical folding structures in multiple regions of the ALN, particularly in the striatal-thalamic circuit and anterior cingulate cortex, could be used to differentiate BD patients from healthy controls and unaffected siblings. We concluded that the cortical folding structures of ALN can provide potential biomarkers for clinical diagnosis of BD and differentiation from the unaffected siblings.

Diffusion Tensor Magnetic Resonance Imaging for Differentiating Multiple System Atrophy Cerebellar Type and Spinocerebellar Ataxia Type 3.

Multiple system atrophy cerebellar type (MSA-C) and spinocerebellar ataxia type 3 (SCA3) demonstrate similar manifestations, including ataxia, pyramidal and extrapyramidal signs, as well as atrophy and signal intensity changes in the cerebellum and brainstem. MSA-C and SCA3 cannot be clinically differentiated through T1-weighted magnetic resonance imaging (MRI) alone; therefore, clinical consensus criteria and genetic testing are also required. Here, we used diffusion tensor imaging (DTI) to measure water molecular diffusion of white matter and investigate the difference between MSA-C and SCA3. Four measurements were calculated from DTI images, including fractional anisotropy (FA), axial diffusivity (AD), radial diffusivity (RD), and mean diffusivity (MD). Fifteen patients with MSA-C, 15 patients with SCA3, and 30 healthy individuals participated in this study. Both patient groups demonstrated a significantly decreased FA but a significantly increased AD, RD, and MD in the cerebello-ponto-cerebral tracts. Moreover, patients with SCA3 demonstrated a significant decrease in FA but more significant increases in AD, RD, and MD in the cerebello-cerebral tracts than patients with MSAC. Our results may suggest that FA and MD can be effectively used for differentiating SCA3 and MSA-C, both of which are cerebellar ataxias and have many common atrophied regions in the cerebral and cerebellar cortex.

Early detection of periodic sharp wave complexes on EEG by independent component analysis in patients with Creutzfeldt-Jakob disease.

Sporadic Creutzfeldt-Jakob disease (sCJD) is the most common human prion disease. EEG is the method of choice to support the diagnosis of a human prion disease. Periodic sharp wave complexes (PSWCs) on the EEG usually indicate a progressive stage of CJD. However, PSWCs only become obvious at around 8 to 12 weeks after the onset of clinical symptoms, and in a few cases, even later. Independent component analysis (ICA) is a new technique to separate statistically independent components from a mixture of data. This study recruited seven patients who fit the criteria of CJD between 2002 and 2005 and 10 patients with Alzheimer's disease (AD) as control subjects. Using an ICA algorithm, we were able to split typical PSWCs into several independent temporal components in conjunction with spatial maps. The PSWCs were not observed in the initial EEG studies of patients with either AD or CJD. However, the ICA algorithm was able to extract periodic discharges and epileptiform discharges from raw EEG of patients with CJD at as early as 3 to 5 weeks after disease onset. Such discharges otherwise could hardly be discerned by visual inspection. In conclusion, ICA may increase the sensitivity of EEG and facilitate the early diagnosis of CJD.

Impaired Efficiency and Resilience of Structural Network in Spinocerebellar Ataxia Type 3.

Background: Recent studies have shown that the patients with spinocerebellar ataxia type 3 (SCA3) may not only have disease involvement in the cerebellum and brainstem but also in the cerebral regions. However, the relations between the widespread degenerated brain regions remains incompletely explored. Methods: In the present study, we investigate the topological properties of the brain networks of SCA3 patients (n = 40) constructed based on the correlation of three-dimensional fractal dimension values. Random and targeted attacks were applied to measure the network resilience of normal and SCA3 groups. Results: The SCA3 networks had significantly smaller clustering coefficients (P < 0.05) and global efficiency (P < 0.05) but larger characteristic path length (P < 0.05) than the normal controls networks, implying loss of small-world features. Furthermore, the SCA3 patients were associated with reduced nodal betweenness (P < 0.001) in the left supplementary motor area, bilateral paracentral lobules, and right thalamus, indicating that the motor control circuit might be compromised. Conclusions: The SCA3 networks were more vulnerable to targeted attacks than the normal controls networks because of the effects of pathological topological organization. The SCA3 revealed a more sparsity and disrupted structural network with decreased values in the largest component size, mean degree, mean density, clustering coefficient, and global efficiency and increased value in characteristic path length. The cortico-cerebral circuits in SCA3 were disrupted and segregated into occipital-parietal (visual-spatial cognition) and frontal-pre-frontal (motor control) clusters. The cerebellum of SCA3 were segregated from cerebellum-temporal-frontal circuits and clustered into a frontal-temporal cluster (cognitive control). Therefore, the disrupted structural network presented in this study might reflect the clinical characteristics of SCA3.

Aberrant Sensory Gating of the Primary Somatosensory Cortex Contributes to the Motor Circuit Dysfunction in Paroxysmal Kinesigenic Dyskinesia.

Paroxysmal kinesigenic dyskinesia (PKD) is conventionally regarded as a movement disorder (MD) and characterized by episodic hyperkinesia by sudden movements. However, patients of PKD often have sensory aura and respond excellently to antiepileptic agents. PRRT2 mutations, the most common genetic etiology of PKD, could cause epilepsy syndromes as well. Standing in the twilight zone between MDs and epilepsy, the pathogenesis of PKD is unclear. Gamma oscillations arise from the inhibitory interneurons which are crucial in the thalamocortical circuits. The role of synchronized gamma oscillations in sensory gating is an important mechanism of automatic cortical inhibition. The patterns of gamma oscillations have been used to characterize neurophysiological features of many neurological diseases, including epilepsy and MDs. This study was aimed to investigate the features of gamma synchronizations in PKD. In the paired-pulse electrical-stimulation task, we recorded the magnetoencephalographic data with distributed source modeling and time-frequency analysis in 19 patients of newly-diagnosed PKD without receiving pharmacotherapy and 18 healthy controls. In combination with the magnetic resonance imaging, the source of gamma oscillations was localized in the primary somatosensory cortex. Somatosensory evoked fields of PKD patients had a reduced peak frequency (p < 0.001 for the first and the second response) and a prolonged peak latency (the first response p = 0.02, the second response p = 0.002), indicating the synchronization of gamma oscillation is significantly attenuated. The power ratio between two responses was much higher in the PKD group (p = 0.013), indicating the incompetence of activity suppression. Aberrant gamma synchronizations revealed the defective sensory gating of the somatosensory area contributes the pathogenesis of PKD. Our findings documented disinhibited cortical function is a pathomechanism common to PKD and epilepsy, thus rationalized the clinical overlaps of these two diseases and the therapeutic effect of antiepileptic agents for PKD. There is a greater reduction of the peak gamma frequency in PRRT2-related PKD than the non-PRRT PKD group (p = 0.028 for the first response, p = 0.004 for the second response). Loss-of-function PRRT2 mutations could lead to synaptic dysfunction. The disinhibiton change on neurophysiology reflected the impacts of PRRT2 mutations on human neurophysiology.

Topographic brain mapping of the international cooperative ataxia rating scale. A positron emission tomography study.

The International Cooperative Ataxia Rating Scale (ICARS) is a 100-point semiquantitative scale designed primarily to assess cerebellar dysfunction. However, little is known of the metric properties of this scale. We assessed the ICARS by rating the severity of cerebellar dysfunction in 27 patients with spinocerebellar ataxias (SCA), three patients with sporadic olivopontocerebellar ataxia and 24 healthy control subjects. [(18)F]-fluorodeoxyglucose (FDG) positron emission tomography (PET) study was also performed on each subject. The statistical parametric mapping analyses revealed a significant correlation between the ICARS scores and functional impairment of the frontal regions within SCA patients. The glucose metabolism in the cerebellum, thalamus and caudate nucleus had significant differences between SCA patients and healthy control subjects. The results suggested that the clinical severity of SCA patients correlated with the functional impairment in the frontal regions, the targets of cerebellar efferent projections.