65 research outputs found
Forward and Backward Modelling: From Single Cells to Neural Population and Back
Some aspects of forward and backward neural modelling are discussed, showing, that the neural mass models may provide a “golden midway” between the detailed conductance based neuron models and the oversimplified models, dealing with the input–output transformations only. Our analysis combines historical perspectives and recent developments concerning neural mass models as a third option for modelling large neural populations and inclusion of detailed anatomical data into them. The current source density analysis and the geometrical assumption behind the different methods, as an inverse modelling tool for determination of the sources of the local field potential is discussed, with special attention to the recent results about source localization on single neurons. These new applications may pave the way to the emergence of a new field of micro-electric imaging
How to find a unicorn: a novel model-free, unsupervised anomaly detection method for time series
Recognition of anomalous events is a challenging but critical task in many
scientific and industrial fields, especially when the properties of anomalies
are unknown. In this paper, we present a new anomaly concept called "unicorn"
or unique event and present a new, model-independent, unsupervised detection
algorithm to detect unicorns. The Temporal Outlier Factor (TOF) is introduced
to measure the uniqueness of events in continuous data sets from dynamic
systems. The concept of unique events differs significantly from traditional
outliers in many aspects: while repetitive outliers are no longer unique
events, a unique event is not necessarily outlier in either pointwise or
collective sense; it does not necessarily fall out from the distribution of
normal activity. The performance of our algorithm was examined in recognizing
unique events on different types of simulated data sets with anomalies and it
was compared with the standard Local Outlier Factor (LOF). TOF had superior
performance compared to LOF even in recognizing traditional outliers and it
also recognized unique events that LOF did not. Benefits of the unicorn concept
and the new detection method were illustrated by example data sets from very
different scientific fields. Our algorithm successfully recognized unique
events in those cases where they were already known such as the gravitational
waves of a black hole merger on LIGO detector data and the signs of respiratory
failure on ECG data series. Furthermore, unique events were found on the LIBOR
data set of the last 30 years
Hierarchically Organized Minority Games
In this paper a hierarchical extension of the Minority Game is defined and
studied. Numerical simulations show a special type of emergent global behavior
between separated parts of the hierarchical structure, connected only through a
normalized mean field quantity.Comment: 8 page
Atomi- és mágneses szerkezetek neutrondiffrakciós vizsgálata = Neutron diffraction study of atomic and magnetic structures
Különböző, modern technológiákkal előállított polikristályos anyagok atomi és mágneses szerkezetének jellemzőit határoztuk meg neutrondiffrakciós mérések Rietveld-módszerrel történő illesztésével. Megállapítottuk, hogy a Sc-mal adalékolt hexaferritben alacsony hőmérsékleten inkommenzurábilis mágneses szerkezet alakul ki. A periódushosszra 98 Angström adódott, a kúp nyílásszögére pedig 40 fokot kaptunk. Kimutattuk, hogy a FeAl2 ötvözet anomális mágneses viselkedését inkommenzurábilis mágneses szerkezete okozza, szemben az irodalomban elterjedt spinüveg állapottal. A töltésrendeződés okozta rácstorzulás - kristály-szimmetriaváltozások - és a lehetséges töltés-és mágneses rendeződést tanulmányoztuk a hőmérséklet függvényében különböző összetételű Bi-alapú manganát-oxid perovszkitokban. Nem-lineáris optikai tulajdonságokkal rendelkező ittrium-aluminumborát kristály szerkezeti paramétereit határoztuk meg Er ill. Yb dópolás hatására. Különböző összetételű nátrumboroszilikát alapű üvegeket állítottunk elő, és a szerkezet jellemzőit vizsgáltuk neutrondiffrakciós módszerrel és a kísérleti adatok fordított Monte Carlo (RMC) szimulációjával. Meghatároztuk a hálószerkezet legfontosabb paramétereit, a parciális atomi párkorrelációs függvényeket, a kötéstávolságokat, a koordinációs számokat, a szerkezetet felépítő egységeket, és egyszerűbb összetételekre a kötésszög- és gyűrűeloszlást is. Sikeresen adalékoltunk UO3-at az üvegbe, és azt tapasztaltuk, hogy az urán beépül a hálószerkezetbe és stabilizálja az üveg szerkezetét. | We have determined the characteristic atomic and magnetic structure parameters for various polycrystalline materials prepared by novel techniques using neutron and x-ray diffraction experimental techniques, and Rietveld analysis data treatment. Formation of an incommensurate magnetic order with 98 ? periodicity length and 40? cone angle has been established in the Sc-substituted hexaferrite. The anomalous magnetic behaviour of FeAl2 alloy was explained by an incommensurate magnetic structure instead of the commonly accepted spin glass structure. Lattice distortion, crystal symmetry changes and charge-magnetic ordering effects were analysed in Bi-based manganese oxide perovskites in dependence of temperature. Changes in lattice parameters and atomic positions were analysed in Er and Yb substituted Yttrium-Aluminum borates. Sodium borosilicate matrix glasses are known as most suitable materials for radioactive waste material storage. We have successfully prepared these matrix glasses with various compositions, and the network structure was analysed by reverse Monte Carlo (RMC) simulation of the neutron diffraction spectra. Several partial atomic pair correlation functions have been revieled, and the characteristic parameters were determined, like the atomic bond distances, coordination numbers, the basic structural units, and for the simple glasses the bond angle- and the ring size distributions, as well. It was found that addition of UO3 stabilizes the network structure
The Retinal TNAP
Accumulating evidence from recent literature underline the important roles of tissue non specific alkaline phosphatase (TNAP) in diverse functions as well as diseases of the nervous system. Exploration of TNAP in well characterized neural circuits such as the retina, might significantly advance our understanding regarding neural TNAP’s roles. This chapter reviews the scarce literature as well as our findings on retinal TNAP. We found that retinal TNAP activity was preserved and followed diverse patterns throughout vertebrate evolution. We have consistently observed TNAP activity (1) in retinal vessels, (2) in photoreceptors and (3) in the majority of the studied species in the outer (OPL) and inner plexiform layers (IPL), where synaptic transmission occurs. Importantly, in some species the IPL exhibits several TNAP positive strata. These strata exactly corresponded those seen after quadruple immunohistochemistry with four canonical IPL markers (tyrosine hydroxylase, choline acetyltransferase, calretinin, protein kinase C α). Diabetes results in diminishing retinal TNAP activity before changes in canonical markers
Optical Imaging of Intrinsic Neural Signals and Simultaneous MicroECoG Recording Using Polyimide Implants
This paper presents the simultaneous use of intrinsic optical signal imaging (iOS) and micro-electrocorticography (μECoG) techniques by introducing a transparent polymer based microelectrode array into the optical recording chamber used in vivo functional mapping experiments in anaesthetized cat. The robustness of its site impedance was proven in electrochemical impedance spectroscopy. To demonstrate the feasibility of the combined optical-electrical recording, we have run several stimulus protocols and measured the evoked optical and electrical responses of the visual cortex
Mental and emotional representations of “weight loss”: free-word association networks in members of bariatric surgery-related social media communities
Background: Mindset and communication barriers may hinder the acceptance of bariatric surgery (BS) by the eligible patient population.
Objectives: To improve the understanding of expectations, opinions, emotions, and attitudes toward weight loss among patients with obesity.
Setting: Switzerland, Germany, Austria.
Methods: Survey data collected from BS-related social media communities (n = 1482). Participants were asked to write 5 words that first came to their mind about "weight loss," and to select 2 emotions, which best described their corresponding feelings. Demographic and obesity-related data were collected. Cognitive representations were constructed based on the co-occurrence network of associations, using validated data-driven methodology.
Results: Respondents were Caucasian (98%), female (94%), aged 42.5 ± 10.1 years, current/highest lifetime body mass index = 36.9 ± 9/50.7 ± 8.7 kg/m2. The association network analysis revealed the following 2 cognitive modules: benefit-focused (health, attractiveness, happiness, agility) and procedure-focused (effort, diet, sport, surgery). Patients willing to undergo BS were more benefit-focused (odds ratio [OR] = 2.4, P = .02) and expressed more "hope" (OR = 142, P < .001). History of BS was associated with higher adherence to the procedure-focused module (OR = 2.3, P < .001), and with increased use of the emotions "gratitude" (OR = 107, P < .001), "pride" (OR = 15, P < .001), and decreased mention of "hope" (OR = .03, P < .001).
Conclusion: Patients with obesity in our study tend to think about weight loss along 2 cognitive schemes, either emphasizing its expected benefits or focusing on the process of achieving it. Benefit-focused respondents were more likely to consider BS, and to express hope rather than gratitude or pride. Novel communication strategies may increase the acceptance of BS by incorporating weight loss-related cognitive and emotional content stemming from patients' free associations
Complete Inference of Causal Relations between Dynamical Systems
From philosophers of ancient times to modern economists, biologists and other
researchers are engaged in revealing causal relations. The most challenging
problem is inferring the type of the causal relationship: whether it is uni- or
bi-directional or only apparent - implied by a hidden common cause only. Modern
technology provides us tools to record data from complex systems such as the
ecosystem of our planet or the human brain, but understanding their functioning
needs detection and distinction of causal relationships of the system
components without interventions. Here we present a new method, which
distinguishes and assigns probabilities to the presence of all the possible
causal relations between two or more time series from dynamical systems. The
new method is validated on synthetic datasets and applied to EEG
(electroencephalographic) data recorded in epileptic patients. Given the
universality of our method, it may find application in many fields of science
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