Steady-state visual-evoked potential (SSVEP)-based brain-computer interfaces (BCIs) have generated significant interest due to their high information transfer rate (ITR). Due to the amplitude-frequency characteristic of the SSVEP, the flickering frequency of an SSVEP-based BCI is typically lower than 20 Hz to achieve a high SNR. However, a visual flicker with a flashing frequency below the critical flicker-fusion frequency often makes subjects feel flicker jerky and causes visual discomfort. This study presents a novel technique using high duty-cycle visual flicker to decrease user's visual discomfort. The proposed design uses LEDs flashing at 13.16 Hz, driven by flickering sequences consisting of repetitive stimulus cycles with a duration T (T = 76 ms). Each stimulus cycle included an ON state with a duration T(ON) and an OFF state with a duration T(OFF) (T = T(ON) + T(OFF)), and the duty cycle, defined as T(ON)/T, varied from 10.5% to 89.5%. This study also includes a questionnaire survey and analyzes the SSVEPs induced by different duty-cycle flickers. An 89.5% duty-cycle flicker, reported as a comfortable flicker, was adopted in a phase-tagged SSVEP system. Six subjects were asked to sequentially input a sequence of cursor commands with the 25.08-bits/min ITR.
Event-related desynchronization/synchronization (ERD/ERS) is a technique to quantify subject's nonphase-locked neural activities underlying specific frequency bands, reactive to external/internal stimulus. However, conventional ERD/ERS studies usually utilize fixed frequency band determined from one or few channels to filter whole-head EEG/MEG data, which may inevitably include task-unrelated signals and result in underestimation of reactive oscillatory activities in multichannel studies. In this study, we adopted multivariate empirical mode decomposition (MEMD) to extract beta-related oscillatory activities in performing self-paced right and left index-finger lifting tasks. The MEMD extracts common modes from all channels in same-index intrinsic mode functions (IMFs) which allows the temporal-frequency features among different channels can be compared in each subband. The beta-band oscillatory activities were further bandpass filtered within trial-specific beta bands determined from sensorimotor-related channels (C3 and C4), and then rectified using amplitude modulation method to detect trial-by-trial beta rebound (BR) values in ERS time courses. The validity of the MEMD approach in BR values extraction has been demonstrated in multichannel EEG study which showed larger BR values than conventional ERS technique. The MEMD-based method enables the trial-by-trial extraction of sensorimotor oscillatory activities which might allow the exploration of subtle brain dynamics in future studies.
Dear Editor, Primary mucosal melanoma is a rare subtype of melanoma that carries poor prognosis. Traditional treatment options of mucosal melanoma are surgery, radiation, and chemotherapy; but the overall survival remains low. 1 Cytotoxic T-lymphocyte associated protein 4 (CLTA-4) and programmed cell death protein 1 (PD-1), both inhibitory immune checkpoints commonly seen on activated T cells, have been found to be promising targets for treatment of advanced cancers. 2 However, the efficacy and response to immunotherapy in mucosal melanoma remains unknown. Herein, we report a case involving a patient, who was a 70-year-old male and referred to Taipei Medical University Hospital with confirmed diagnosis of mucosa melanoma over hard plate of mouth. The patient was admitted and subjected to anti-PD-1 immunotherapy (pembrolizumab 200 mg every 3 weeks) (Figure 1A). Serial imaging of primary malignant melanoma of the hard palate showed that the tumor size gradually decreased after treatment with pembrolizumab, suggesting partial response/stable disease secondary to continuous immunotherapy (Figure 1B). However, after seventh cycle of treatment, magnetic resonance imaging (MRI) revealed enlarged previous known metastatic lesions and new tumor nodules in brain (Figure 1B). The patient received stereotactic radiation therapy before treatment cycle 14 (Figure 1A). Although the primary metastatic brain lesions were smaller and stationary after radiotherapy, the following brain MRI displayed several hyperdensity masses in the right frontal lobe with perifocal edema and mild mass effect (Figure 1B). Subsequently, patient suffered from infection and respiratory distress and died 2 months after 17 th cycle of pembrolizumab therapy. To monitor changes in patient's circulating T-cell repertoire at each cycle of immunotherapy, high-throughput TCRβ sequencing of peripheral blood mononuclear cells (PBMCs), isolated from the patient's peripheral blood, was performed using a rapid amplification of 5′ complemen-This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
ObjectiveThe timing and nature of surgical intervention for semisolid abnormalities are dependent upon distinguishing between adenocarcinoma-in-situ (AIS), minimally invasive adenocarcinoma (MIA), and invasive adenocarcinoma (INV). We sought to develop and evaluate a quantitative imaging method to determine invasiveness of small, ground-glass lesions on computed tomography (CT) chest scans.MethodsThe study comprised 268 patients from 4 institutions with resected (<=3 cm) semisolid lesions with confirmed histopathological diagnosis of MIA/AIS or INV. A total of 248 radiomic texture features from within the tumor nodule (intratumoral) and adjacent to the nodule (peritumoral) were extracted from manually annotated lung nodules of chest CT scans. The datasets were randomly divided, with 40% of patients used for training and 60% used for testing the machine classifier (Training DTrain, N=106; Testing, DTest, N=162).ResultsThe top five radiomic stable features included four intratumoral (Laws and Haralick feature families) and one peritumoral feature within 3 to 6 mm of the nodule (CoLlAGe feature family), which successfully differentiated INV from MIA/AIS nodules with an AUC of 0.917 [0.867-0.967] on DTrain and 0.863 [0.79-0.931] on DTest. The radiomics model successfully differentiated INV from MIA cases (<1 cm AUC: 0.76 [0.53-0.98], 1-2 cm AUC: 0.92 [0.85-0.98], 2-3 cm AUC: 0.95 [0.88-1]). The final integrated model combining the classifier with the radiologists’ score gave the best AUC on DTest (AUC=0.909, p<0.001).ConclusionsAddition of advanced image analysis via radiomics to the routine visual assessment of CT scans help better differentiate adenocarcinoma subtypes and can aid in clinical decision making. Further prospective validation in this direction is warranted.
Olfactory dysfunction is related to several clinical neurodegenerative diseases, such as Alzheimer's disease, multiple sclerosis, degenerative ataxias, Parkinson's disease, and so on. Owing to the individual difference in the sensory adaption of human smell function, the olfactory responses usually exhibit large inter-individual difference and change over time after repeated stimulations. The traditional analysis tools, such as statistical parametric mapping (SPM) in functional magnetic resonance imaging technique (fMRI) analysis, utilize the paradigm-based linear correlation and statistical techniques to discriminate the activation areas from background activities. However, these traditional approaches extract olfactory-induced responses using the stereotypic template or paradigm generated model. The olfactory-induced hemodynamic responses affected by internal/external events, such as changes of smell fatigue and attention, are not considered and therefore could result in misleading results. In this paper, owing to the stochastic characteristic of olfactory-induced responses, we adopted multivariate empirical mode decomposition (MEMD) to extract olfactory-induced hemodynamic responses in MRI blood-oxygenlevel dependent (BOLD) signals. The MEMD is an efficient data-driven approach to extract nonlinear and non-stationary signals, which is an improved method to expand traditional empirical mode decomposition (EMD) from one channel to multi-channel processing. We applied MEMD to decompose time series of BOLD signals from each slice into multivariate intrinsic mode functions (IMF). The MEMD enables common features of different scales in an image slice to be arranged in distinct IMFs. Each IMF is an analytic, self-constructed, well-defined, and data-driven function with time-varying frequencies. Each IMF was examined by checking its correlation with the paradigm-generated template. The task-related IMFs were chosen to reconstruct olfactory-induced hemodynamic responses. The group analysis of MEMD-processed data showed olfactory-induced activations in the anterior cingulate cortex and middle frontal gyrus. INDEX TERMS Multivariate empirical mode decomposition, olfactory, functional magnetic resonance imaging.
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