scholarly journals Multichannel Sleep Spindle Detection using Sparse Low-Rank Optimization

2017 ◽  
Author(s):  
Ankit Parekh ◽  
Ivan W. Selesnick ◽  
Ricardo S. Osorio ◽  
Andrew W. Varga ◽  
David M. Rapoport ◽  
...  
Keyword(s):  
Detection Method ◽  
Single Channel ◽  
Low Rank ◽  
Sleep Spindles ◽  
Transient Component ◽  
Oscillatory Component ◽  
Scalp Eeg ◽  
Spindle Activity ◽  
Zero Baseline ◽  
Global And Local

AbstractBackgroundWe propose a multichannel spindle detection method that detects global and local spindle activity across all channels of scalp EEG in a single runNew MethodUsing a non-linear signal model, which assumes the multichannel EEG to be a sum of a transient component and an oscillatory component, we propose a multichannel transient separation algorithm. Consecutive overlapping blocks of the multichannel oscillatory component are assumed to be low-rank whereas the transient component is assumed to be piecewise constant with a zero baseline. The estimated multichannel oscillatory component is used in conjunction with a bandpass filter and the Teager operator for detecting sleep spindlesResults and comparison with other methodsSeveral examples are shown to illustrate the utility of the proposed method in detecting global and local spindle activity. The proposed method is applied to two publicly available databases and compared with 7 existing single-channel automated detectors. F1scores for the proposed spindle detection method averaged 0.66 (0.02) and 0.62 (0.06) for the two databases, respectively. For an overnight 6 channel EEG signal, the proposed algorithm takes about 4 minutes to detect sleep spindles simultaneously across all channels with a single setting of corresponding algorithmic parametersConclusionsThe proposed method aims to mimic and utilize, for better spindle detection, a particular human expert behavior where the decision to mark a spindle event may be subconsciously influenced by the presence of a spindle in EEG channels other than the central channel visible on a digital screen

Snowflake Removal for Videos via Global and Local Low-Rank Decomposition

2018 ◽  
Vol 20 (10) ◽  
pp. 2659-2669 ◽  
Author(s):  
Jiandong Tian ◽  
Zhi Han ◽  
Weihong Ren ◽  
Xiai Chen ◽  
Yandong Tang
Keyword(s):  
Low Rank ◽  
Rank Decomposition ◽  
Global And Local ◽  
Low Rank Decomposition

scholarly journals Fault Detection Method Based on Global-Local Marginal Discriminant Preserving Projection for Chemical Process

Processes ◽  
2022 ◽  
Vol 10 (1) ◽  
pp. 122
Author(s):  
Yang Li ◽  
Fangyuan Ma ◽  
Cheng Ji ◽  
Jingde Wang ◽  
Wei Sun
Keyword(s):  
Feature Extraction ◽  
Fault Detection ◽  
Chemical Process ◽  
Detection Method ◽  
Detection Performance ◽  
Detection Methods ◽  
Normal Operation ◽  
Discriminative Feature ◽  
Inherent Feature ◽  
Global And Local

Feature extraction plays a key role in fault detection methods. Most existing methods focus on comprehensive and accurate feature extraction of normal operation data to achieve better detection performance. However, discriminative features based on historical fault data are usually ignored. Aiming at this point, a global-local marginal discriminant preserving projection (GLMDPP) method is proposed for feature extraction. Considering its comprehensive consideration of global and local features, global-local preserving projection (GLPP) is used to extract the inherent feature of the data. Then, multiple marginal fisher analysis (MMFA) is introduced to extract the discriminative feature, which can better separate normal data from fault data. On the basis of fisher framework, GLPP and MMFA are integrated to extract inherent and discriminative features of the data simultaneously. Furthermore, fault detection methods based on GLMDPP are constructed and applied to the Tennessee Eastman (TE) process. Compared with the PCA and GLPP method, the effectiveness of the proposed method in fault detection is validated with the result of TE process.

CALCIUM CHANNEL CURRENTS IN NEURONES FROM LOCUST (SCHISTOCERCA GREGARIA) THORACIC GANGLIA

1993 ◽  
Vol 177 (1) ◽  
pp. 201-221 ◽  
Author(s):  
H. A. Pearson ◽  
G. Lees ◽  
D. Wray
Keyword(s):  
Calcium Channel ◽  
Single Channel ◽  
Schistocerca Gregaria ◽  
Patch Clamp Technique ◽  
Whole Cell ◽  
Transient Component ◽  
Thoracic Ganglia ◽  
Steady State Inactivation ◽  
Inward Currents ◽  
Channel Currents

1. Using the patch-clamp technique, Ca2+ channel currents were recorded from neurones freshly isolated from the thoracic ganglia of the desert locust Schistocerca gregaria. 2. In solutions containing 10 mmol l-1 Ba2+ we observed high-voltage-activated whole-cell inward currents with sustained and transient components, both of which had similar steady-state inactivation properties. 3. Substitution of Ca2+ for Ba2+ was found to reduce whole-cell currents, whereas removal of monovalent cations had no effect. 4. Cd2+ (1 mmol l-1) completely blocked the whole-cell current, but at 10 micromolar preferentially inhibited the sustained component without affecting the transient component. 5. Verapamil (1 micromolar) inhibited both current components but appeared to be more selective for the sustained component, whereas nitrendipine (1 micromolar) had no effect on either component. 6. A single-channel recording suggested that the transient component was carried by a low- conductance channel. 7. Certain compounds with insecticidal action (ryanodine, S-bioallethrin, deltamethrin and avermectin) did not affect calcium channel currents in these cells. 8. These data suggest that there are two types of Ca2+ channels present in locust neurones. These channel types have properties differing from the T-, L- and N-type channels found in vertebrates and, furthermore, were not targets for the insecticides we tested.

scholarly journals Single-Channel Speech Enhancement Based on Adaptive Low-Rank Matrix Decomposition

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 37066-37076
Author(s):  
Chao Li ◽  
Ting Jiang ◽  
Sheng Wu ◽  
Jianxiao Xie
Keyword(s):  
Speech Enhancement ◽  
Single Channel ◽  
Matrix Decomposition ◽  
Low Rank ◽  
Rank Matrix ◽  
Low Rank Matrix

scholarly journals Ocular fixations and presaccadic potentials to explain pareidolias in Parkinson’s disease

2020 ◽  
Vol 2 (1) ◽  
Author(s):  
Gajanan S Revankar ◽  
Noriaki Hattori ◽  
Yuta Kajiyama ◽  
Tomohito Nakano ◽  
Masahito Mihara ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Eye Tracking ◽  
Eye Movement ◽  
Visual Processing ◽  
Top Down ◽  
Scalp Eeg ◽  
Wide Range ◽  
Saccade Size ◽  
Global And Local

Abstract In Parkinson’s disease, a precursor phenomenon to visual hallucinations presents as ‘pareidolias’ which make ambiguous forms appear meaningful. To evoke and detect pareidolias in patients, a noise pareidolia test was recently developed, although its task-dependent mechanisms are yet to be revealed. When subjected to this test, we hypothesized that patients exhibiting pareidolias would show altered top-down influence of visual processing allowing us to demonstrate the influence of pareidolic illusionary behaviour in Parkinson’s disease patients. To that end, we evaluated eye-movement strategies and fixation-related presaccadic activity on scalp EEG when participants performed the test. Twelve healthy controls and 21 Parkinson’s disease patients, evaluated for cognitive, visuo-spatial and executive functions, took a modified computer-based version of the noise pareidolia test in a free-viewing EEG eye-tracking experiment. Eye-tracking metrics (fixation-related durations and counts) documented the eye movement behaviour employed in correct responses (face/noise) and misperceptions (pareidolia/missed) during early and late visual search conditions. Simultaneously, EEG recorded the presaccadic activity in frontal and parietal areas of the brain. Based on the noise pareidolia test scores, we found certain Parkinson’s disease patients exhibited pareidolias whereas others did not. ANOVA on eye-tracking data showed that patients dwelled significantly longer to detect faces and pareidolias which affected both global and local search dynamics depending on their visuo-perceptual status. Presaccadic activity in parietal electrodes for the groups was positive for faces and pareidolias, and negative for noise, though these results depended mainly on saccade size. However, patients sensitive to pareidolias showed a significantly higher presaccadic potential on frontal electrodes independent of saccade sizes, suggesting a stronger frontal activation for pareidolic stimuli. We concluded with the following interpretations (i) the noise pareidolia test specifically characterizes visuo-perceptual inadequacies in patients despite their wide range of cognitive scores, (ii) Parkinson’s disease patients dwell longer to converge attention to pareidolic stimuli due to abnormal saccade generation proportional to their visuo-perceptual deficit during early search, and during late search, due to time-independent alteration of visual attentional network and (iii) patients with pareidolias show increased frontal activation reflecting the allocation of attention to irrelevant targets that express the pareidolic phenomenon. While the disease per se alters the visuo-perceptual and oculomotor dynamics, pareidolias occur in Parkinson’s disease due to an abnormal top-down modulation of visual processing that affects visual attention and guidance to ambiguous stimuli.

scholarly journals Detection of Hypoglycemia Using Measures of EEG Complexity in Type 1 Diabetes Patients

Entropy ◽  
2020 ◽  
Vol 22 (1) ◽  
pp. 81 ◽  
Author(s):  
Maria Rubega ◽  
Fabio Scarpa ◽  
Debora Teodori ◽  
Anne-Sophie Sejling ◽  
Christian S. Frandsen ◽  
...  
Keyword(s):  
Type 1 Diabetes ◽  
Single Channel ◽  
Permutation Entropy ◽  
Eeg Signals ◽  
Scalp Eeg ◽  
Power Spectral ◽  
Eeg Changes ◽  
Eeg Recordings ◽  
Clamp Study

Previous literature has demonstrated that hypoglycemic events in patients with type 1 diabetes (T1D) are associated with measurable scalp electroencephalography (EEG) changes in power spectral density. In the present study, we used a dataset of 19-channel scalp EEG recordings in 34 patients with T1D who underwent a hyperinsulinemic–hypoglycemic clamp study. We found that hypoglycemic events are also characterized by EEG complexity changes that are quantifiable at the single-channel level through empirical conditional and permutation entropy and fractal dimension indices, i.e., the Higuchi index, residuals, and tortuosity. Moreover, we demonstrated that the EEG complexity indices computed in parallel in more than one channel can be used as the input for a neural network aimed at identifying hypoglycemia and euglycemia. The accuracy was about 90%, suggesting that nonlinear indices applied to EEG signals might be useful in revealing hypoglycemic events from EEG recordings in patients with T1D.

scholarly journals Sleep spindles, ripples, and interictal epileptiform discharges in the human anterior and mediodorsal thalamus

2021 ◽  
Author(s):  
Orsolya Szalardy ◽  
Peter Simor ◽  
Peter Przemyslaw Ujma ◽  
Zsofia Jordan ◽  
Laszlo Halasz ◽  
...  
Keyword(s):  
Neural Plasticity ◽  
Nrem Sleep ◽  
Cortical Activity ◽  
Sleep Spindles ◽  
Time Frequency ◽  
Scalp Eeg ◽  
Epileptiform Discharges ◽  
Interictal Epileptiform Discharges ◽  
Human Thalamus ◽  
Result Show

Sleep spindles are major oscillatory components of Non-Rapid Eye Movement (NREM) sleep, reflecting hyperpolarization-rebound sequences of thalamocortical neurons, the inhibition of which is caused by the NREM-dependent activation of GABAergic neurons in the reticular thalamic nucleus. Reports suggest a link between sleep spindles and several forms of interictal epileptic discharges (IEDs) which are considered as expressions of pathological off-line neural plasticity in the central nervous system. Here we investigated the relationship between thalamic sleep spindles, IEDs and ripples in the anterior and mediodorsal nuclei (ANT and MD) of epilepsy patients. Whole-night LFP from the ANT and MD were co-registered with scalp EEG/polysomnography by using externalized leads in 15 epilepsy patients undergoing Deep Brain Stimulation protocol. Slow (~12 Hz) and fast (~14 Hz) sleep spindles were present in the human ANT and MD. Roughly, one third of thalamic sleep spindles were associated with IEDs or ripples. Both IED- and ripple-associated spindles were longer than pure spindles. IED-associated thalamic sleep spindles were characterized by broadband increase in thalamic and cortical activity, both below and above the spindle frequency range, whereas ripple-associated thalamic spindles exceeded pure spindles in terms of 80-200 Hz thalamic, but not cortical activity as indicated by time-frequency analysis. These result show that thalamic spindles coupled with IEDs are reflected at the scalp slow and beta-gamma oscillation as well. IED density during sleep spindles in the MD, but not in the ANT was identified as correlates of years spent with epilepsy, whereas no signs of pathological processes were correlated with measures of ripple and spindle association. Furthermore, the density of ripple-associated sleep spindles in the ANT showed a positive correlation with general intelligence. Our findings indicate the complex and multifaceted role of the human thalamus in sleep spindle-related physiological and pathological neural plasticity.

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