scholarly journals INTELLIGENCE LEVEL MIGHT BE PREDICTED BY THE CHARACTERISTICS OF EEG SIGNALS AT SPECIFIC FREQUENCIES AND BRAIN REGIONS

2021 ◽  
pp. 2140047
Author(s):  
SONG LUO ◽  
RUI CHEN ◽  
ZHENGTING YANG ◽  
KUN LI
Keyword(s):  
Total Energy ◽  
Distribution Patterns ◽  
Brain Regions ◽  
Information Flows ◽  
Research Subjects ◽  
Eeg Signals ◽  
Long Distance ◽  
Adult Intelligence Scale ◽  
Intellectual Activity ◽  
Intelligence Level

The total energy the brain consumed and the intensities of information flows across different brain regions in an intellectual activity may help to explain an individual’s intelligence level. To verify this assumption, 43 students aged 18–25 were recruited as the research subjects. Their intelligence quotients (IQ) were scored by using Wechsler Adult Intelligence Scale (WAIS), while their electroencephalogram (EEG) signals were recorded simultaneously by using Neuroscan system. The total energy and distribution patterns of EEG signals were acquired in Curry 8.0. The intensities of information flow across different brain regions were measured by Phase Slope Index (PSI). 20 channels and 190 channel combinations were selected for data analysis. The results show that the IQ score negatively correlates to the EEG energy and positively correlates to the intensities of information flows at specific frequency bands in specific channel pairs, especially in some long distance (18–24[Formula: see text]cm) channel pairs.

scholarly journals Disentangling relationships among eastern Mediterranean Cymbalaria including description of a novel species from the southern Peloponnese (Greece)

2021 ◽  
Vol 307 (2) ◽  
Author(s):  
Pau Carnicero ◽  
Núria Garcia-Jacas ◽  
Llorenç Sáez ◽  
Theophanis Constantinidis ◽  
Mercè Galbany-Casals
Keyword(s):  
Eastern Mediterranean ◽  
Phylogenetic Analyses ◽  
Taxonomic Revision ◽  
Distribution Patterns ◽  
Morphological Characters ◽  
Molecular Data ◽  
Morphological Data ◽  
Long Distance ◽  
Aegean Islands ◽  
Molecular Phylogenetic

AbstractThe eastern Mediterranean basin hosts a remarkably high plant diversity. Historical connections between currently isolated areas across the Aegean region and long-distance dispersal events have been invoked to explain current distribution patterns of species. According to most recent treatments, at least two Cymbalaria species occur in this area, Cymbalaria microcalyx and C. longipes. The former comprises several intraspecific taxa, treated at different ranks by different authors based on morphological data, evidencing the need of a taxonomic revision. Additionally, some populations of C. microcalyx show exclusive morphological characters that do not match any described taxon. Here, we aim to shed light on the systematics of eastern Mediterranean Cymbalaria and to propose a classification informed by various sources of evidence. We performed molecular phylogenetic analyses using ITS, 3’ETS, ndhF and rpl32-trnL sequences and estimated the ploidy level of some taxa performing relative genome size measures. Molecular data combined with morphology support the division of traditionally delimited C. microcalyx into C. acutiloba, C. microcalyx and C. minor, corresponding to well-delimited nrDNA lineages. Furthermore, we propose to combine C. microcalyx subsp. paradoxa at the species level. A group of specimens previously thought to belong to Cymbalaria microcalyx constitute a well-defined phylogenetic and morphological entity and are described here as a new species, Cymbalaria spetae. Cymbalaria longipes is non-monophyletic, but characterized by being glabrous and diploid, unlike other eastern species. The nrDNA data suggest at least two dispersals from the mainland to the Aegean Islands, potentially facilitated by marine regressions.

DESIGN AND IMPLEMENTATION OF WIRELESS MULTI-CHANNEL EEG RECORDING SYSTEM AND STUDY OF EEG CLUSTERING METHOD

2006 ◽  
Vol 18 (06) ◽  
pp. 276-283 ◽  
Author(s):  
ROBERT LIN ◽  
REN-GUEY LEE ◽  
CHWAN-LU TSENG ◽  
YAN-FA WU ◽  
JOE-AIR JIANG
Keyword(s):  
Energy Operator ◽  
Digital Processing ◽  
Recording System ◽  
Ar Model ◽  
Characteristic Matrix ◽  
Eeg Signal ◽  
Eeg Signals ◽  
Long Distance ◽  
Communication Module ◽  
Processing Circuit

A multi-channel wireless EEG (electroencephalogram) acquisition and recording system is developed in this work. The system includes an EEG sensing and transmission unit and a digital processing circuit. The former is composed of pre-amplifiers, filters, and gain amplifiers. The kernel of the later digital processing circuit is a micro-controller unit (MCU, TI-MSP430), which is utilized to convert the EEG signals into digital signals and fulfill the digital filtering. By means of Bluetooth communication module, the digitized signals are sent to the back-end such as PC or PDA. Thus, the patient's EEG signal can be observed and stored without any long cables such that the analogue distortion caused by long distance transmission can be reduced significantly. Furthermore, an integrated classification method, consisting of non-linear energy operator (NLEO), autoregressive (AR) model, and bisecting k-means algorithm, is also proposed to perform EEG off-line clustering at the back-end. First, the NLEO algorithm is utilized to divide the EEG signals into many small signal segments according to the features of the amplitude and frequency of EEG signals. The AR model is then applied to extract two characteristic values, i.e., frequency and amplitude (peak to peak value), of each segment and to form characteristic matrix for each segment of EEG signal. Finally, the improved modified k-means algorithm is utilized to assort similar EEG segments into better data classification, which allows accessing the long-term EEG signals more quickly.

scholarly journals Evaluasi Program English Massive Dalam Upaya Peningkatan Kapasitas Masyarakat di Kota Kediri Tahun 2017-2019

2020 ◽  
Vol 12 (1) ◽  
pp. 58
Author(s):  
Anselmus Edwin Dwi Cahya ◽  
Rizqi Bachtiar
Keyword(s):  
Qualitative Research ◽  
Public Awareness ◽  
The Internet ◽  
Research Subjects ◽  
Input Process ◽  
Long Distance ◽  
Process Indicator ◽  
The Impact ◽  
Input Indicator ◽  
Process Product

Penelitian ini bertujuan untuk mengetahui pelaksanaan program English Massive (E-Mas) dalam upaya peningkatan kapasitas masyarakat di Kota Kediri tahun 2017-2019 dengan teori Evaluasi model CIPP menurut Stufflebeam diantaranya: Context; Input, Process, Product. Penelitian ini menggunakan metode penelitian kualitatif deskriptif. Subjek penelitian diantaranya penyelenggara program, partisipan, tutor dengan menggunakan teknik purposive. Hasil Penelitian menunjukkan evaluasi program English Massive berdasarkan: Context, latar belakang dan tujuan ialah ingin memberdayakan masyarakat melalui pembelajaran Bahasa Inggris supaya meningkatkan daya saing dan kapasitas masyarakat kota Kediri; syarat E-Mas mudah dan target sasaran seluruh warga Kota Kediri. Input, kesesuaian partisipan telah sesuai namun hanya kategori children memiliki jumlah partisipan tiggi; Tutor disediakan oleh Dinas Pendidikan dan sesuai dengan kriteria namun jumlah tutor menurun; materi yang diberikan sesuai dengan silabus dan kemampuan partisipan dengan fokus conversation dan speaking; anggaran telah mencukupi untuk kebutuhan dan operasional program; sarana dan prasarana sudah cukup memadai karena dikelola oleh masyarakat sendiri; informasi sudah jelas diberikan melalui sosialisasi, media sosial dan internet. Process, penjadwalan telah sesuai sebab jadwal direncanakan oleh partisipan dan tutor; proses pembelajaran cukup efektif melalui diskusi dan fun game; aktivitas selain pembelajaran yaitu outing class, COIN EMAS, outbond dan sebagainya; hambatan yaitu kesadaran masyarakat kurang, adanya kesibukan, spot kurang kondusif, jarak yang jauh antara spot dengan tempat tinggal tutor, honor tidak cair tiap bulan, modul tidak dibagikan ke partisipan. Product, dampak yang dirasakan partisipan adanya peningkatan kemampuan partisipan dalam berbahasa inggris; meningkatkan IPM Kota Kediri.This study aims to investigate the implementation of the English Massive (E-Mas) program as an effort to improve social capacity in Kediri City, year 2017-2019 by utilising Stufflebeams’s theory of evaluation. This research uses descriptive qualitative research methods. Research subjects include program organizers, participants, tutors by using purposive techniques. The results of the study show that the background and purpose of the English Massive program based on the first indicator in which Context is to empower the society through learning English in order to improve the competitiveness and capacity of the Kediri’s citizens; E-Mas requirements are easy and target for all residents of Kediri City. Based on Input Indicator, participants are arguably fit with the standar but only the children category has a high number of participants; Tutors were provided by the Education Office (Dinas Pendidikan); the material provided is in accordance with the syllabus and the ability of participants focusing on conversation and speaking. The budget is sufficient for program’s expenses and operations; facilities and infrastructure are good enough because they are managed and provided also by the society itself; information has clearly been provided through outreach, social media and the internet. Based on Process Indicator, scheduling is appropriate because the schedule is planned by participants and tutors; the learning process is quite effective through discussion and fun games; activities other than learning, namely outing class, COIN EMAS, outbound and so on; the obstacles are lack of public awareness, busyness, less conducive spot, long distance between spot and tutor's residence, monthly non-payment of honorarium, modules are not distributed to participants. Product Indicator, the impact felt by the participants is an increase in the ability of participants in speaking English as well as improving the HDI of Kediri City.

scholarly journals Brain regions associated with visual cues are important for bird migration

2015 ◽  
Vol 11 (11) ◽  
pp. 20150678 ◽  
Author(s):  
Orsolya Vincze ◽  
Csongor I. Vágási ◽  
Péter L. Pap ◽  
Gergely Osváth ◽  
Anders Pape Møller
Keyword(s):  
Visual Cues ◽  
Optic Lobe ◽  
Brain Size ◽  
Relative Size ◽  
Bird Species ◽  
Interspecific Variation ◽  
Brain Regions ◽  
Long Distance ◽  
Migration Distance ◽  
Whole Brain

Long-distance migratory birds have relatively smaller brains than short-distance migrants or residents. Here, we test whether reduction in brain size with migration distance can be generalized across the different brain regions suggested to play key roles in orientation during migration. Based on 152 bird species, belonging to 61 avian families from six continents, we show that the sizes of both the telencephalon and the whole brain decrease, and the relative size of the optic lobe increases, while cerebellum size does not change with increasing migration distance. Body mass, whole brain size, optic lobe size and wing aspect ratio together account for a remarkable 46% of interspecific variation in average migration distance across bird species. These results indicate that visual acuity might be a primary neural adaptation to the ecological challenge of migration.

Australian Indigenous Ochres

2021 ◽  
Author(s):  
Jillian Huntley
Keyword(s):  
Cultural Landscapes ◽  
Cultural Practices ◽  
Distribution Patterns ◽  
Archaeological Sites ◽  
Theoretical Frameworks ◽  
Long Distance ◽  
Novel Studies ◽  
Trade And Exchange ◽  
Key Terms

Aboriginal Australians use ochre in varied cultural practices. It is found in the earliest to most recent archaeological sites and geographically across the wide-ranging geological and climatic contexts of the continent. Ochre’s importance in Aboriginal societies, coupled with its availability across Australia and its long-term durability, has led to a ubiquitous archaeological presence with considerable potential to study past cultural landscapes and intergroup interactions, including long-distance trade and exchange. Concentrating on scientific sourcing analyses, this article highlights the benefits of archaeopigment research, defining key terms (ochre, provenience, and provenance) and the technicalities of sourcing studies before discussing theoretical frameworks used in interpretations of ochre distribution patterns. The article argues that as we move away from novel studies on ethnographically well-known source locations into applied research, exceptional Australian records are well placed to investigate territoriality, mobility, intergroup and human–landscape interactions, and to explore the catalysts driving cultural diversity.

scholarly journals Historical biogeography of two cosmopolitan families of flowering plants: Annonaceae and Rhamnaceae

2004 ◽  
Vol 359 (1450) ◽  
pp. 1495-1508 ◽  
Author(s):  
J. E. Richardson ◽  
L. W. Chatrou ◽  
J. B. Mols ◽  
R. H. J. Erkens ◽  
M. D. Pirie
Keyword(s):  
Dna Sequences ◽  
Phylogenetic Trees ◽  
Phylogenetic Analyses ◽  
Plastid Dna ◽  
Distribution Patterns ◽  
Historical Biogeography ◽  
Rate Heterogeneity ◽  
Long Distance ◽  
Fossil Calibration ◽  
Dispersal Capability

Annonaceae are a pantropically distributed family found predominantly in rainforests, so they are megathermal taxa, whereas Rhamnaceae are a cosmopolitan family that tend to be found in xeric regions and may be classified as mesothermal. Phylogenetic analyses of these families are presented based on rbcL and trn L–F plastid DNA sequences. Likelihood ratio tests revealed rate heterogeneity in both phylogenetic trees and they were therefore made ultrametric using non–parametric rate smoothing and penalized likelihood. Divergence times were then estimated using fossil calibration points. The historical biogeography of these families that are species rich in different biomes is discussed and compared with other published reconstructions. Rhamnaceae and most lineages within Annonaceae are too young to have had their distribution patterns influenced by break–up of previously connected Gondwanan landmasses. Contrasts in the degree of geographical structure between these two families may be explained by differences in age and dispersal capability. In both groups, long–distance dispersal appears to have played a more significant role in establishing modern patterns than had previously been assumed. Both families also contain examples of recent diversification of species–rich lineages. An understanding of the processes responsible for shaping the distribution patterns of these families has contributed to our understanding of the historical assembly of the biomes that they occupy.

Reconstruction of Neural Activity from EEG Data Using Dynamic Spatiotemporal Constraints

2016 ◽  
Vol 26 (07) ◽  
pp. 1650026 ◽  
Author(s):  
E. Giraldo-Suarez ◽  
J. D. Martinez-Vargas ◽  
G. Castellanos-Dominguez
Keyword(s):  
Spatial Resolution ◽  
Neural Activity ◽  
Focal Epilepsy ◽  
Experimental Testing ◽  
Brain Activity ◽  
Brain Regions ◽  
Basis Set ◽  
Eeg Signals ◽  
Reconstruction Performance ◽  
Eeg Data

We present a novel iterative regularized algorithm (IRA) for neural activity reconstruction that explicitly includes spatiotemporal constraints, performing a trade-off between space and time resolutions. For improving the spatial accuracy provided by electroencephalography (EEG) signals, we explore a basis set that describes the smooth, localized areas of potentially active brain regions. In turn, we enhance the time resolution by adding the Markovian assumption for brain activity estimation at each time period. Moreover, to deal with applications that have either distributed or localized neural activity, the spatiotemporal constraints are expressed through [Formula: see text] and [Formula: see text] norms, respectively. For the purpose of validation, we estimate the neural reconstruction performance in time and space separately. Experimental testing is carried out on artificial data, simulating stationary and non-stationary EEG signals. Also, validation is accomplished on two real-world databases, one holding Evoked Potentials and another with EEG data of focal epilepsy. Moreover, responses of functional magnetic resonance imaging for the former EEG data have been measured in advance, allowing to contrast our findings. Obtained results show that the [Formula: see text]-based IRA produces a spatial resolution that is comparable to the one achieved by some widely used sparse-based estimators of brain activity. At the same time, the [Formula: see text]-based IRA outperforms other similar smooth solutions, providing a spatial resolution that is lower than the sparse [Formula: see text]-based solution. As a result, the proposed IRA is a promising method for improving the accuracy of brain activity reconstruction.

scholarly journals Neurological Disorder Detection of Brain Abnormal Activities Using a New Enhanced Computer-aided Model

2021 ◽  
Vol 2128 (1) ◽  
pp. 012017
Author(s):  
D Shoieb ◽  
S Youssef
Keyword(s):  
Brain Regions ◽  
Autism Spectrum ◽  
Diagnostic Model ◽  
Discrete Wavelet ◽  
Eeg Signals ◽  
Clinical Interviews ◽  
Number Of Children ◽  
Average Accuracy ◽  
Proposed Model ◽  
Diagnostic Time

Abstract In the field of neurodevelopmental disorders, Autism Spectrum Disorders (ASD) are recognized as one of the dramatically increased etiologically and clinically heterogeneous diseases. Although, increasing the number of children who have difficulties in communication or suffer from sudden malfunction of the brain, the current diagnostic approaches for those kind of disease are time-consuming and are mainly based on clinical interviews. In this paper, a new enhanced diagnostic model is introduced addressing many of the challenges which threats the analysis of Electroencephalography (EEG) signals. A preprocessing stage is proposed to choose the key segment of EEG channel and remove the artifacts in the EEG signals to enhance their quality. The proposed model uses a set of discriminative features based on discrete wavelet transform (DWT) such as skewness, standard division, shannon entropy and relative wave energy. Also, extracting cross correction between brain regions to detect abnormal connectivity and synchronization. Two EEG datasets are used to verify the accuracy of the proposed model. The fusion of two EEG dataset helps in building a more generalized mode to diagnose epilepsy and ASD. In the fused dataset, the combination of the mentioned features and Random Forest have produced a very promising diagnosis result with minimum diagnostic time, with an average accuracy equals to 96.78%. The proposed model obtained better classification accuracy compared to the existing methods.

scholarly journals fMRI-guided white matter connectivity in fluid and crystallized cognitive abilities in healthy adults

2020 ◽  
Author(s):  
Yunglin Gazes ◽  
Jayant Sakhardande ◽  
Ashley Mensing ◽  
Qolamreza Razlighi ◽  
Ann Ohkawa ◽  
...  
Keyword(s):  
White Matter ◽  
Episodic Memory ◽  
Diffusion Tensor ◽  
Mean Diffusivity ◽  
Brain Regions ◽  
Long Distance ◽  
White Matter Tracts ◽  
Percent Signal Change ◽  
Signal Change ◽  
Fluid Abilities

AbstractThis study examined within-subject differences among three fluid abilities that decline with age: reasoning, episodic memory and processing speed, compared with vocabulary, a crystallized ability that is maintained with age. The data were obtained from the Reference Ability Neural Network (RANN) study from which 221 participants had complete behavioral data for all 12 cognitive tasks, three per ability, along with fMRI and diffusion weighted imaging data. We used fMRI task activation to guide white matter tractography, and generated mean percent signal change in the regions associated with the processing of each ability along with diffusion tensor imaging measures, fractional anisotropy (FA) and mean diffusivity (MD), for each cognitive ability. Qualitatively brain regions associated with vocabulary were more localized and lateralized to the left hemisphere whereas the fluid abilities were associated with brain activations that were more distributed across the brain and bilaterally situated. Using continuous age, we observed smaller correlations between MD and age for white matter tracts connecting brain regions associated with the vocabulary ability than that for the fluid abilities, suggesting that vocabulary white matter tracts were better maintained with age. Furthermore, after multiple comparisons correction, the mean percent signal change for the episodic memory showed positive associations with behavioral performance, and the associations between MD and percent signal change differed by age such that, when divided into three age groups to further explore this interaction, only the oldest age group show a significant negative correlation between the two brain measures. Overall, the vocabulary ability may be better maintained with age due to the more localized brain regions involved, which places smaller reliance on long distance white matter tracts for signal transduction. These results support the hypothesis that functional activation and white matter structures underlying the vocabulary ability contribute to the ability’s greater resistance against aging.

Sign in / Sign up

Export Citation Format

Share Document