Drug-induced parkinsonism (DIP) is the second-most-common etiology of parkinsonism in the elderly after Parkinson's disease (PD). Many patients with DIP may be misdiagnosed with PD because the clinical features of these two conditions are indistinguishable. Moreover, neurological deficits in patients with DIP may be severe enough to affect daily activities and may persist for long periods of time after the cessation of drug taking. In addition to typical antipsychotics, DIP may be caused by gastrointestinal prokinetics, calcium channel blockers, atypical antipsychotics, and antiepileptic drugs. The clinical manifestations of DIP are classically described as bilateral and symmetric parkinsonism without tremor at rest. However, about half of DIP patients show asymmetrical parkinsonism and tremor at rest, making it difficult to differentiate DIP from PD. The pathophysiology of DIP is related to drug-induced changes in the basal ganglia motor circuit secondary to dopaminergic receptor blockade. Since these effects are limited to postsynaptic dopaminergic receptors, it is expected that presynaptic dopaminergic neurons in the striatum will be intact. Dopamine transporter (DAT) imaging is useful for diagnosing presynaptic parkinsonism. DAT uptake in the striatum is significantly decreased even in the early stage of PD, and this characteristic may help in differentiating PD from DIP. DIP may have a significant and longstanding effect on patients' daily lives, and so physicians should be cautious when prescribing dopaminergic receptor blockers and should monitor patients' neurological signs, especially for parkinsonism and other movement disorders.

Cortical oscillations play a fundamental role in organizing large-scale functional brain networks. Noninvasive brain stimulation with temporally patterned waveforms such as repetitive transcranial magnetic stimulation (rTMS) and transcranial alternating current stimulation (tACS) have been proposed to modulate these oscillations. Thus, these stimulation modalities represent promising new approaches for the treatment of psychiatric illnesses in which these oscillations are impaired. However, the mechanism by which periodic brain stimulation alters endogenous oscillation dynamics is debated and appears to depend on brain state. Here, we demonstrate with a static model and a neural oscillator model that recurrent excitation in the thalamo-cortical circuit, together with recruitment of cortico-cortical connections, can explain the enhancement of oscillations by brain stimulation as a function of brain state. We then performed concurrent invasive recording and stimulation of the human cortical surface to elucidate the response of cortical oscillations to periodic stimulation and support the findings from the computational models. We found that (1) stimulation enhanced the targeted oscillation power, (2) this enhancement outlasted stimulation, and (3) the effect of stimulation depended on behavioral state. Together, our results show successful target engagement of oscillations by periodic brain stimulation and highlight the role of nonlinear interaction between endogenous network oscillations and stimulation. These mechanistic insights will contribute to the design of adaptive, more targeted stimulation paradigms.

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These reference values are necessary for advancing the field of neuromuscular ultrasound, because they facilitate studies of the median nerve in conditions such as entrapment, hereditary neuropathy, acquired neuropathy, and intraneural masses.

Mutations in five PARK genes (SNCA, PARKIN, DJ-1, PINK1, and LRRK2) are well-established genetic causes of Parkinson disease (PD). Recently, G2385R substitution in LRRK2 has been determined as a susceptibility allele in Asian PD. The objective of this study is to determine the frequency of mutations in these PARK genes in a Korean early-onset Parkinson disease (EOPD) cohort. The authors sequenced 35 exons in SNCA, PARKIN, DJ-1, PINK1, and LRRK2 in 72 unrelated EOPD (age-at-onset ≤50) recruited from ten movement disorders clinics in South Korea. Gene dosage change of Neurogenetics

Our initial hybrid PET-MRI experience increased diagnostic yields for detection of potential epileptic lesions. This may be due to the unique advantage of improved co-registration and simultaneous review of both structural and functional data.

In the recent MRI scanning, ultra-high-field (7T) MR imaging provides higher resolution and better tissue contrast compared to routine 3T MRI, which may help in more accurate and early brain diseases diagnosis. However, currently, 7T MRI scanners are more expensive and less available at clinical and research centers. These motivate us to propose a method for the reconstruction of images close to the quality of 7T MRI, called 7T-like images, from 3T MRI, to improve the quality in terms of resolution and contrast. By doing so, the post-processing tasks, such as tissue segmentation, can be done more accurately and brain tissues details can be seen with higher resolution and contrast. To do this, we have acquired a unique dataset which includes paired 3T and 7T images scanned from same subjects, and then propose a hierarchical reconstruction based on group sparsity in a novel multi-level Canonical Correlation Analysis (CCA) space, to improve the quality of 3T MR image to be 7T-like MRI. First, overlapping patches are extracted from the input 3T MR image. Then, by extracting the most similar patches from all the aligned 3T and 7T images in the training set, the paired 3T and 7T dictionaries are constructed for each patch. It is worth noting that, for the training, we use pairs of 3T and 7T MR images from each training subject. Then, we propose multi-level CCA to map the paired 3T and 7T patch sets to a common space to increase their correlations. In such space, each input 3T MRI patch is sparsely represented by the 3T dictionary and then the obtained sparse coefficients are used together with the corresponding 7T dictionary to reconstruct the 7T-like patch. Also, to have the structural consistency between adjacent patches, the group sparsity is employed. This reconstruction is performed with changing patch sizes in a hierarchical framework. Experiments have been done using 13 subjects with both 3T and 7T MR images. The results show that our method outperforms previous methods and is able to recover better structural details. Also, to place our proposed method in a medical application context, we evaluated the influence of post-processing methods such as brain tissue segmentation on the reconstructed 7T-like MR images. Results show that our 7T-like images lead to higher accuracy in segmentation of white matter (WM), gray matter (GM), cerebrospinal fluid (CSF), and skull, compared to segmentation of 3T MR images.