Temat: brain network - Prolib Integro

Skocz do pozycji: 1.

Tytuł:: Personal identification based on brain networks of EEG signals
Autorzy:: Kong, W.
Jiang, B.
Fan, Q.
Zhu, L.
Wei, X.
Tematy:: electroencephalogram signal
personal identification
brain network
phase synchronization
elektroencefalogram
identyfikacja osobowa
sieć mózgowa
synchronizacja fazy; Pokaż więcej
Wydawca:: Uniwersytet Zielonogórski. Oficyna Wydawnicza
Powiązania:: https://bibliotekanauki.pl/articles/329856.pdf Link otwiera się w nowym oknie
Opis:: Personal identification is particularly important in information security. There are numerous advantages of using electroencephalogram (EEG) signals for personal identification, such as uniqueness and anti-deceptiveness. Currently, many researchers focus on single-dataset personal identification, instead of the cross-dataset. In this paper, we propose a method for cross-dataset personal identification based on a brain network of EEG signals. First, brain functional networks are constructed from the phase synchronization values between EEG channels. Then, some attributes of the brain networks including the degree of a node, the clustering coefficient and global efficiency are computed to form a new feature vector. Lastly, we utilize linear discriminant analysis (LDA) to classify the extracted features for personal identification. The performance of the method is quantitatively evaluated on four datasets involving different cognitive tasks: (i) a four-class motor imagery task dataset in BCI Competition IV (2008), (ii) a two-class motor imagery dataset in the BNCI Horizon 2020 project, (iii) a neuromarketing dataset recorded by our laboratory, (iv) a fatigue driving dataset recorded by our laboratory. Empirical results of this paper show that the average identification accuracy of each data set was higher than 0.95 and the best one achieved was 0.99, indicating a promising application in personal identification.
Dostawca treści:: Biblioteka Nauki

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Tytuł:: Matrix-variate regression for sparse, low-rank estimation of brain connectivities associated with a clinical outcome
Autorzy:: Brzyski, Damian
Goñi, Joaquín
Ances, Beau
Harezlak, Jaroslaw
Randolph, Timothy W
Hu, Xixi
Opis:: Objective: We address the problem of finding brain connectivities that are associated with a clinical outcome or phenotype. Methods: The proposed framework regresses a (scalar) clinical outcome on matrix-variate predictors which arise in the form of brain connectivity matrices. For example, in a large cohort of subjects we estimate those regions of functional connectivities that are associated with neurocognitive scores. We approach this high-dimensional yet highly structured estimation problem by formulating a regularized estimation process that results in a low-rank coefficient matrix having a sparse set of nonzero entries which represent regions of biologically relevant connectivities. In contrast to the recent literature on estimating a sparse, low-rank matrix from a single noisy observation, our scalar-on-matrix regression framework produces a data-driven extraction of structures that are associated with a clinical response. The method, called Sp arsity I nducing N uclear- N orm E stimato r (SpINNEr), simultaneously constrains the regression coefficient matrix in two ways: a nuclear norm penalty encourages low-rank structure while an ℓ1 norm encourages entry-wise sparsity. Results: Our simulations show that SpINNEr outperforms other methods in estimation accuracy when the response-related entries (representing the brain's functional connectivity) are arranged in well-connected communities. SpINNEr is applied to investigate associations between HIV-related outcomes and functional connectivity in the human brain. Conclusion and Significance: Overall, this work demonstrates the potential of SpINNEr to recover sparse and low-rank estimates under scalar-on-matrix regression framework.
Dostawca treści:: Repozytorium Uniwersytetu Jagiellońskiego

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Skocz do pozycji: 3.

Tytuł:: High and low-level brain network models
Autorzy:: Danielak, Tomasz
Opis:: Przy coraz bardziej zaawansowanych i dokładnych metodach do pomiaru aktywności mózgu, potrzebujemy nowych sposobów na opracowanie danych. Chciałbym zaprezentować różne obliczeniowe sposoby modelowania mózgu oparte na neuronauce sieciowej. To dziedzina teorii sieci z szerszego obszaru systemów złożonych, rozwiniętych przez nauki inżynieryjne i fizykę. To stosunkowo nowe podejście pozwala nam uzyskać nową perspektywę na interakcje jakie zachodzą pomiędzy obszarami w mózgu, komunikacje pomiędzy nimi oraz zależności funkcjonalne. Wszystkie te rzeczy znajdują zastosowanie w wyjaśnianiu pracy mózgu, a co ważniejsze w zastosowaniach klinicznych leczenia uszkodzeń mózgu, neuropatologii i chorób.
With more advanced methods to measure brain activity, in a more detailed way, we need new approaches to elaborate the data. Here, I want to present different computational approaches to modelling the brain, on high and low levels, based on network neuroscience framework. It is a domain of network theory from the field of complex systems, heavily developed by engineering and physical studies. This relatively new approach provides us with new perspectives on brain regions interactions, communications and functions, which occur in the brain during cognition. All of these find their applications in explaining new aspects in the brain’s work and more importantly in clinical treatment of brain damages, neuropathologies and diseases.
Dostawca treści:: Repozytorium Uniwersytetu Jagiellońskiego

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Skocz do pozycji: 4.

Tytuł:: Neuronalne podstawy efektu pozytywności w procesie starzenia się - badanie z wykorzystaniem funkcjonalnego rezonansu magnetycznego i kwestionariuszy
Neural bases of positivity bias in ageing - an fMRI and questionnaire study
Autorzy:: Wielgus, Magdalena
Opis:: Studies on affective functioning in ageing provide evidence for age-related changes in the preference of positive information often referred to as “positivity bias”. This effect has been found in studies on attention and memory, but its neural bases are still less discovered.Our study aimed at investigating positivity effect on the level of neuronal activity, self-report and behaviour. For this purpose, we collected functional magnetic resonance, behavioural and questionnaire data from 12 older patients and 12 younger healthy volunteers. In the scanning session participants completed a modified version of affective Lexical Decision Task. We have found positivity bias in the evaluation of affective stimuli, but not in the self-reported affect and the ability to experience pleasure. Neuroimaging results revealed that younger adults showed enhanced activity in the salience network while detecting relevant stimuli. In the older group that network was less activated, and the older participants also committed more errors at detecting the target cues. This difference might have contributed to the attenuated emotion processing in the older group that we observed in the task.
Badania nad emocjami w procesie starzenia się donoszą, iż osoby starsze wraz z wiekiem zaczynają wykazywać tendencję do preferowania informacji pozytywnych, która w literaturze określana jest jako tzw. „efekt pozytywności”. Obecność efektu pozytywności w późnej dorosłości potwierdzona została w badaniach nad uwagą i pamięcią, jednak neuronalne podstawy tego zjawiska nie zostały do tej pory całkowicie poznane.Niniejsze badanie miało na celu zbadanie efektu pozytywności przejawiającego się w aktywności neuronalnej, ocenie bodźców o emocjonalnym charakterze oraz w deklarowanym afekcie i zdolności odczuwania przyjemności. W eksperymencie wzięło udział 12 pacjentów w wieku starszym oraz 12 młodych ochotników. Przeprowadzono badania kwestionariuszowe, pomiary behawioralne oraz badanie z wykorzystaniem funkcjonalnego rezonansu magnetycznego, podczas którego uczestnicy wykonywali zmodyfikowaną (afektywną) wersję zadania decyzji leksykalnych.Badanie potwierdziło obecność efektu pozytywności w ocenie bodźców afektywnych, jednak nie w deklarowanym afekcie i zdolności do odczuwania przyjemności. Wyniki neuroobrazowania wykazały, że aktywność neuronalna podczas rozwiązywania poznawczego aspektu zadania była zwiększona w tzw. „sieci istotności” (ang. salience network). W grupie osób starszych sieć ta była mniej aktywna, co wiązało się również z większą ilością pomyłek w wykrywaniu istotnych w zadaniu bodźców. Różnica w poziomie zasobów poznawczych obu grup mogła przyczynić się do osłabionego przetwarzania emocji podczas wykonywania zadania, które zaobserwowaliśmy w starszej grupie.
Dostawca treści:: Repozytorium Uniwersytetu Jagiellońskiego

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Tytuł:: Brain, mind and modern human identity – dilemmas and solutions
Autorzy:: Błaszak, Maciej
Tematy:: predictive mind
bayesian brain
salience network
central executive network
default mode network
human cognitive evolution; Pokaż więcej
Wydawca:: Polska Akademia Nauk. Czytelnia Czasopism PAN
Powiązania:: https://bibliotekanauki.pl/articles/703008.pdf Link otwiera się w nowym oknie
Opis:: Human brain is “the perfect guessing machine” (James V. Stone (2012) Vision and Brain, Cambridge, Mass: The MIT Press, p. 155), trying to interpret sensory data in the light of previous biases or beliefs. Bayesian inference is carried out by three complex networks of the human brain: salience network, central executive network, and default mode network. Their function is analysed both in neurotypical person and Attention Deficit Disorder. Modern human being having predictive brain and overloaded mind must develop social identity, whose evolution went probably through three stages: social selection based on punishment, sexual selection based on reputation, and group selection based on identity.
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 6.

Tytuł:: Zastosowanie metod głębokiego uczenia dla diagnostyki raka mózgu
Application of deep learning methods for the diagnosis of brain cancer
Autorzy:: Jaremko, Hubert
Opis:: The dynamic development of machine learning methods, especially deep learning, allowed their use in the diagnosis of brain diseases. The aim of the study is to develop an application supporting the diagnosis of the three most common brain tumors: meningioma, glioma, and pituitary tumor, along with the differentiation of a healthy brain, with the use of convolutional neural networks. The first part of the work introduces the necessary concepts and the theory behind artificial neural networks, as well as presents a historical outline of magnetic resonance imaging. The second part describes the developed application and the modeling process of the brain cancer classifier. The paper was completed with an analysis of the performance of the model.
Dynamiczny rozwój metod uczenia maszynowego, a zwłaszcza głębokiego uczenia pozwolił na ich wykorzystanie w diagnostyce schorzeń mózgu. Celem pracy jest opracowanie aplikacji wspomagającej diagnostykę trzech najpowszechniej występujących nowotworów mózgu: oponiaka, glejaka oraz guza przysadki wraz z odróżnieniem mózgu zdrowego, przy pomocy konwolucyjnych sieci neuronowych. Pierwsza część pracy wprowadza niezbędne pojęcia oraz teorię stojącą za sztucznymi sieciami neuronowymi, a także przedstawia rys historyczny badań z użyciem rezonansu magnetycznego. Druga część zawiera opis stworzonej aplikacji oraz procesu modelowania klasyfikatora raka mózgu. Praca została zakończona analizą jakości modelu.
Dostawca treści:: Repozytorium Uniwersytetu Jagiellońskiego

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Skocz do pozycji: 7.

Tytuł:: Neuroplasticity and Microglia Functions Applied in Dense Wireless Networks
Autorzy:: Kułacz, Łukasz
Kliks, Adrian
Tematy:: ad-hoc network
brain inspired communication
glial cells
neurons; Pokaż więcej
Wydawca:: Instytut Łączności - Państwowy Instytut Badawczy
Powiązania:: https://bibliotekanauki.pl/articles/308840.pdf Link otwiera się w nowym oknie
Opis:: This paper presents developments in the area of brain-inspired wireless communications relied upon in dense wireless networks. Classic approaches to network design are complemented, ﬁrstly, by the neuroplasticity feature enabling to add the learning ability to the network. Secondly, the microglia ability enabling to repair a network with damaged neurons is considered. When combined, these two functionalities guarantee a certain level of fault-tolerance and self-repair of the network. This work is inspired primarily by observations of extremely energy eﬃcient functions of the brain, and of the role that microglia cells play in the active immune defense system. The concept is veriﬁed by computer simulations, where messages are transferred through a dense wireless network based on the assumption of minimized energy consumption. Simulation encompasses three diﬀerent network topologies which show the impact that the location of microglia nodes and their quantity exerts on network performance. Based on the results achieved, some algorithm improvements and potential future work directions have been identiﬁed.
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 8.

Tytuł:: Mind-body problem : does complexity exist objectively?
Autorzy:: Korzeniewski, Bernard
Opis:: Complexity and related phenomena exist as at least as “objective” and primary aspects/elements of the world as matter, space, and time. On the other hand, space, time, and matter become more and more subjective in modern physics. Complexity causes “something new” to emerge at the level of the whole complex system, which is not present at the level of the elements of this system and cannot be fully reduced to the interactions between these elements. This fact concerns both simple systems, such as atoms composed of a nucleus and electrons or (macro)molecules composed of atoms, as well as very complex systems such as living individuals built of (macro)molecules, organelles, cells, and organs, and conscious brains composed of networks of neurons. In other words, the dynamic complexity consisting of a special concrete spatiotemporal organisation of matter/ energy is as real as space, time, and matter themselves. Therefore, one can speak about the “objective” existence of such a “subjective” phenomenon as (self-)consciousness. The last phenomenon constitutes an aspect, epiphenomenon, or “by-product” of the functional complexity of the (part of the) neural network in the human brain. Self-)consciousness is equivalent to a certain kind of such complexity and must emerge as a necessary aspect of an appropriately organised dynamic neural network. Therefore, for instance, zombies cannot exist or are even nonsensical. Each dynamic state of the neural network underling self-consciousness is univocally related to one psychic state, and inversely. It is postulated that the mind-body problem can be explained/resolved by a special kind of complexity, which consists of recurrent self-reference, directing on itself the “cognitive centre” in the neural network in the human brain.
Dostawca treści:: Repozytorium Uniwersytetu Jagiellońskiego

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Skocz do pozycji: 9.

Tytuł:: Convolutional neural networks for P300 signal detection applied to brain computer interface
Autorzy:: Riyad, Mouad
Khalil, Mohammed
Adib, Abdellah
Tematy:: deep learning
convolutional neural network
brain computer interface
P300
classification; Pokaż więcej
Wydawca:: Sieć Badawcza Łukasiewicz - Przemysłowy Instytut Automatyki i Pomiarów
Powiązania:: https://bibliotekanauki.pl/articles/2141900.pdf Link otwiera się w nowym oknie
Opis:: A Brain‐Computer Interface (BCI) is an instrument capa‐ ble of commanding machine with brain signal. The mul‐ tiple types of signals allow designing many applications like the Oddball Paradigms with P300 signal. We propose an EEG classification system applied to BCI using the con‐ volutional neural network (ConvNet) for P300 problem. The system consists of three stages. The first stage is a Spatiotemporal convolutional layer which is a succession of temporal and spatial convolutions. The second stage contains 5 standard convolutional layers. Finally, a lo‐ gistic regression is applied to classify the input EEG sig‐ nal. The model includes Batch Normalization, Dropout, and Pooling. Also, It uses Exponential Linear Unit (ELU) function and L1‐L2 regularization to improve the lear‐ ning. For experiments, we use the database Dataset II of the BCI Competition III. As a result, we get an F1‐score of 53.26% which is higher than the BN3 model.
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 10.

Tytuł:: Diurnal variations of resting-state fMRI data : a graph-based analysis
Autorzy:: Karwowski, Waldemar
Bohaterewicz, Bartosz
Farahani, Farzad V.
Marek, Tadeusz
Sobczak, Anna
Betzel, Richard F.
D'Esposito, Mark
Douglas, Pamela K.
Fąfrowicz, Magdalena
Opis:: Circadian rhythms (lasting approximately 24 h) control and entrain various physiological processes, ranging from neural activity and hormone secretion to sleep cycles and eating habits. Several studies have shown that time of day (TOD) is associated with human cognition and brain functions. In this study, utilizing a chronotype-based paradigm, we applied a graph theory approach on resting-state functional MRI (rs-fMRI) data to compare whole-brain functional network topology between morning and evening sessions and between morning-type (MT) and evening-type (ET) participants. Sixty-two individuals (31 MT and 31 ET) underwent two fMRI sessions, approximately 1 hour (morning) and 10 h (evening) after their wake-up time, according to their declared habitual sleep-wake pattern on a regular working day. In the global analysis, the findings revealed the effect of TOD on functional connectivity (FC) patterns, including increased small-worldness, assortativity, and synchronization across the day. However, we identified no significant differences based on chronotype categories. The study of the modular structure of the brain at mesoscale showed that functional networks tended to be more integrated with one another in the evening session than in the morning session. Local/regional changes were affected by both factors (i.e., TOD and chronotype), mostly in areas associated with somatomotor, attention, frontoparietal, and default networks. Furthermore, connectivity and hub analyses revealed that the somatomotor, ventral attention, and visual networks covered the most highly connected areas in the morning and evening sessions: the latter two were more active in the morning sessions, and the first was identified as being more active in the evening. Finally, we performed a correlation analysis to determine whether global and nodal measures were associated with subjective assessments across participants. Collectively, these findings contribute to an increased understanding of diurnal fluctuations in resting brain activity and highlight the role of TOD in future studies on brain function and the design of fMRI experiments.
Dostawca treści:: Repozytorium Uniwersytetu Jagiellońskiego

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