scholarly journals Unsupervised Learning of Brain State Dynamics during Emotion Imagination using High-Density EEG

NeuroImage ◽  
2022 ◽  
pp. 118873
Author(s):  
Sheng-Hsiou Hsu ◽  
Yayu Lin ◽  
Julie Onton ◽  
Tzyy-Ping Jung ◽  
Scott Makeig
Keyword(s):  
Unsupervised Learning ◽  
High Density ◽  
Brain State

scholarly journals Unsupervised Learning of Brain State Dynamics during Emotion Imagery using High-Density EEG

2020 ◽  
Author(s):  
Sheng-Hsiou Hsu ◽  
Yayu Lin ◽  
Julie Onton ◽  
Tzyy-Ping Jung ◽  
Scott Makeig
Keyword(s):  
Temporal Dynamics ◽  
Emotional Experience ◽  
High Density ◽  
Supervised Machine Learning ◽  
Data Driven ◽  
Brain State ◽  
Emotion Decoding ◽  
Emotional Imagery ◽  
Time Courses ◽  
Dynamic States

AbstractHere we assume that emotional states correspond to functional dynamic states of brain and body, and attempt to characterize the appearance of these states in high-density scalp electroencephalographic (EEG) recordings acquired from 31 participants during 1-2 hour sessions, each including fifteen 3-5 min periods of self-induced emotion imagination using the method of guided imagery. EEG offers an objective and high-resolution measurement of whatever portion of cortical electrical dynamics is resolvable from scalp recordings. Despite preliminary progress in EEG-based emotion decoding using supervised machine learning methods, few studies have applied data-driven, unsupervised decomposition approaches to investigate the underlying EEG dynamics by characterizing brain temporal dynamics during emotional experience. This study applies an unsupervised approach – adaptive mixture independent component analysis (adaptive mixture ICA, AMICA) that learns a set of ICA models each accounted for portions of a given multi-channel EEG recording. We demonstrate that 20-model AMICA decomposition can identify distinct EEG patterns or dynamic states active during each of the fifteen emotion-imagery periods. The transition in EEG patterns revealed the time-courses of brain-state dynamics during emotional imagery. These time-courses varied across emotions: “grief” and “happiness” showed more abrupt transitions while “contentment” was nearly indistinguishable from the preceding rest period. The spatial distributions of independent components (ICs) of the AMICA models showed higher similarity within-subject across emotions than within-emotion across subjects. No significant differences in IC distributions were found between positive and negative emotions. However, significant changes in IC distributions during emotional imagery compared to rest were identified in brain areas such as the left prefrontal cortex, the posterior cingulate cortex, the motor cortex, and the visual cortex. The study demonstrates the feasibility of AMICA in modeling high-density and nonstationary EEG and its utility in providing data-driven insights into brain state dynamics during self-paced emotional experiences, which have been difficult to measure. This approach can advance our understanding of highly dynamical emotional processes and improve the performance of EEG-based emotion decoding for affective computing and human-computer interaction.

Non-Canonical Microstate Becomes Salient in High Density EEG During Propofol-Induced Altered States of Consciousness

2020 ◽  
Vol 30 (02) ◽  
pp. 2050005 ◽  
Author(s):  
Wen Shi ◽  
Yamin Li ◽  
Zhian Liu ◽  
Jing Li ◽  
Qiang Wang ◽  
...  
Keyword(s):  
Electric Activity ◽  
High Density ◽  
Altered States Of Consciousness ◽  
Brain State ◽  
High Temporal Resolution ◽  
Altered States ◽  
Stable States ◽  
Hilbert Huang Transform ◽  
Multivariate Empirical Mode Decomposition ◽  
States Of Consciousness

Dynamically assessing the level of consciousness is still challenging during anesthesia. With the help of Electroencephalography (EEG), the human brain electric activity can be noninvasively measured at high temporal resolution. Several typical quasi-stable states are introduced to represent the oscillation of the global scalp electric field. These so-called microstates reflect spatiotemporal dynamics of coherent neural activities and capture the switch of brain states within the millisecond range. In this study, the microstates of high-density EEG were extracted and investigated during propofol-induced transition of consciousness. To analyze microstates on the frequency domain, a novel microstate-wise spectral analysis was proposed by the means of multivariate empirical mode decomposition and Hilbert–Huang transform. During the transition of consciousness, a map with a posterior central maximum denoted as microstate F appeared and became salient. The current results indicated that the coverage, occurrence, and power of microstate F significantly increased in moderate sedation. The results also demonstrated that the transition of brain state from rest to sedation was accompanied by significant increase in mean energy of all frequency bands in microstate F. Combined with studies on the possible cortical sources of microstates, the findings reveal that non-canonical microstate F is highly associated with propofol-induced altered states of consciousness. The results may also support the inference that this distinct topography can be derived from canonical microstate C (anterior-posterior orientation). Finally, this study further develops pertinent methodology and extends possible applications of the EEG microstate during propofol-induced anesthesia.

Planar defects in ordered (Ga,In)P

1988 ◽  
Vol 46 ◽  
pp. 902-903
Author(s):  
S. McKernan ◽  
C. B. Carter ◽  
D. Bour ◽  
J. R. Shealy
Keyword(s):  
Electron Diffraction ◽  
Vapor Phase ◽  
Growth Direction ◽  
High Density ◽  
Ordered Structure ◽  
Planar Defects ◽  
Diffraction Patterns ◽  
Ternary Semiconductors ◽  
Anion Species ◽  
Metallic Vapor

The growth of ternary III-V semiconductors by organo-metallic vapor phase epitaxy (OMVPE) is widely practiced. It has been generally assumed that the resulting structure is the same as that of the corresponding binary semiconductors, but with the two different cation or anion species randomly distributed on their appropriate sublattice sites. Recently several different ternary semiconductors including AlxGa1-xAs, Gaxln-1-xAs and Gaxln1-xP1-6 have been observed in ordered states. A common feature of these ordered compounds is that they contain a relatively high density of defects. This is evident in electron diffraction patterns from these materials where streaks, which are typically parallel to the growth direction, are associated with the extra reflections arising from the ordering. However, where the (Ga,ln)P epilayer is reasonably well ordered the streaking is extremely faint, and the intensity of the ordered spot at 1/2(111) is much greater than that at 1/2(111). In these cases it is possible to image relatively clearly many of the defects found in the ordered structure.

Quantitative defect studies in semiconductor TEM samples prepared by low angle ion milling

1995 ◽  
Vol 53 ◽  
pp. 512-513
Author(s):  
L. Mulestagno ◽  
J.C. Holzer ◽  
P. Fraundorf
Keyword(s):  
Sample Preparation ◽  
Milling Time ◽  
High Density ◽  
Low Density ◽  
Ion Milling ◽  
High Quality ◽  
Variable Angle ◽  
Major Disadvantage ◽  
Induced Defects

Due to the wealth of information, both analytical and structural that can be obtained from it TEM always has been a favorite tool for the analysis of process-induced defects in semiconductor wafers. The only major disadvantage has always been, that the volume under study in the TEM is relatively small, making it difficult to locate low density defects, and sample preparation is a somewhat lengthy procedure. This problem has been somewhat alleviated by the availability of efficient low angle milling.Using a PIPS® variable angle ion -mill, manufactured by Gatan, we have been consistently obtaining planar specimens with a high quality thin area in excess of 5 × 104 μm2 in about half an hour (milling time), which has made it possible to locate defects at lower densities, or, for defects of relatively high density, obtain information which is statistically more significant (table 1).

Using the scanning electron microscope for failure analysis of high density magnetic media

1987 ◽  
Vol 45 ◽  
pp. 392-393
Author(s):  
Evelyn R. Ackerman ◽  
Gary D. Burnett
Keyword(s):  
Electron Microscope ◽  
Scanning Electron Microscope ◽  
Failure Analysis ◽  
High Density ◽  
Magnetic Media ◽  
Specific Data ◽  
Retrieval Systems ◽  
Operating Environments ◽  
The Media ◽  
Scanning Electron

Advancements in state of the art high density Head/Disk retrieval systems has increased the demand for sophisticated failure analysis methods. From 1968 to 1974 the emphasis was on the number of tracks per inch. (TPI) ranging from 100 to 400 as summarized in Table 1. This emphasis shifted with the increase in densities to include the number of bits per inch (BPI). A bit is formed by magnetizing the Fe203 particles of the media in one direction and allowing magnetic heads to recognize specific data patterns. From 1977 to 1986 the tracks per inch increased from 470 to 1400 corresponding to an increase from 6300 to 10,800 bits per inch respectively. Due to the reduction in the bit and track sizes, build and operating environments of systems have become critical factors in media reliability.Using the Ferrofluid pattern developing technique, the scanning electron microscope can be a valuable diagnostic tool in the examination of failure sites on disks.

Triglyceride to high density lipoprotein cholesterol ratio, total cholesterol to high density lipoprotein cholesterol ratio and low ankle brachial index in an elderly population

VASA ◽  
2014 ◽  
Vol 43 (3) ◽  
pp. 189-197 ◽  
Author(s):  
Yiqiang Zhan ◽  
Jinming Yu ◽  
Rongjing Ding ◽  
Yihong Sun ◽  
Dayi Hu
Keyword(s):  
High Density Lipoprotein ◽  
Total Cholesterol ◽  
High Density Lipoprotein Cholesterol ◽  
Ankle Brachial Index ◽  
Density Lipoprotein ◽  
High Density ◽  
Lipoprotein Cholesterol ◽  
Lipid Lowering ◽  
Cholesterol Ratio ◽  
Potential Biomarker

Background: The associations of triglyceride (TG) to high-density lipoprotein cholesterol ratio (HDL‑C) and total cholesterol (TC) to HDL‑C ratio and low ankle brachial index (ABI) were seldom investigated. Patients and methods: A population based cross-sectional survey was conducted and 2982 participants 60 years and over were recruited. TG, TC, HDL‑C, and low-density lipoprotein cholesterol (LDL-C) were assessed in all participants. Low ABI was defined as ABI ≤ 0.9 in either leg. Multiple logistic regression models were applied to study the association between TG/HDL‑C ratio, TC/HDL‑C ratio and low ABI. Results: The TG/HDL‑C ratios for those with ABI > 0.9 and ABI ≤ 0.9 were 1.28 ± 1.20 and 1.48 ± 1.13 (P < 0.0001), while the TC/HDL‑C ratios were 3.96 ± 1.09 and 4.32 ± 1.15 (P < 0.0001), respectively. After adjusting for age, gender, body mass index, obesity, current drinking, physical activity, hypertension, diabetes, lipid-lowering drugs, and cardiovascular disease history, the odds ratios (ORs) with 95 % confidence intervals (CIs) of low ABI for TG/HDL‑C ratio and TC/HDL‑C ratio were 1.10 (0.96, 1.26) and 1.34 (1.14, 1.59) in non-smokers. When TC was further adjusted, the ORs (95 % CIs) were 1.40 (0.79, 2.52) and 1.53 (1.21, 1.93) for TG/HDL‑C ratio and TC/HDL‑C ratio, respectively. Non-linear relationships were detected between TG/HDL‑C ratio and TC/HDL‑C ratio and low ABI in both smokers and non-smokers. Conclusions: TC/HDL‑C ratio was significantly associated with low ABI in non-smokers and the association was independent of TC, TG, HDL‑C, and LDL-C. TC/HDL‑C might be considered as a potential biomarker for early peripheral arterial disease screening.

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