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Understanding causal relationships, or effective connectivity, between parts of the brain is of utmost importance because a large part of the brain’s activity is thought to be internally generated and, hence, quantifying stimulus response relationships alone does not fully describe brain dynamics. Past efforts to determine effective connectivity mostly relied on model based approaches such as Granger causality or dynamic causal modeling. Transfer entropy (TE) is an alternative measure of effective connectivity based on information theory. TE does not require a model of the interaction and is inherently non-linear. We investigated the applicability of TE as a metric in a test for effective connectivity to electrophysiological data based on simulations and magnetoencephalography (MEG) recordings in a simple motor task. In particular, we demonstrate that TE improved the detectability of effective connectivity for non-linear interactions, and for sensor level MEG signals where linear methods are hampered by signal-cross-talk due to volume conduction.
Information theory allows us to investigate information processing in neural systems in terms of information transfer, storage and modification. Especially the measure of information transfer, transfer entropy, has seen a dramatic surge of interest in neuroscience. Estimating transfer entropy from two processes requires the observation of multiple realizations of these processes to estimate associated probability density functions. To obtain these necessary observations, available estimators typically assume stationarity of processes to allow pooling of observations over time. This assumption however, is a major obstacle to the application of these estimators in neuroscience as observed processes are often non-stationary. As a solution, Gomez-Herrero and colleagues theoretically showed that the stationarity assumption may be avoided by estimating transfer entropy from an ensemble of realizations. Such an ensemble of realizations is often readily available in neuroscience experiments in the form of experimental trials. Thus, in this work we combine the ensemble method with a recently proposed transfer entropy estimator to make transfer entropy estimation applicable to non-stationary time series. We present an efficient implementation of the approach that is suitable for the increased computational demand of the ensemble method's practical application. In particular, we use a massively parallel implementation for a graphics processing unit to handle the computationally most heavy aspects of the ensemble method for transfer entropy estimation. We test the performance and robustness of our implementation on data from numerical simulations of stochastic processes. We also demonstrate the applicability of the ensemble method to magnetoencephalographic data. While we mainly evaluate the proposed method for neuroscience data, we expect it to be applicable in a variety of fields that are concerned with the analysis of information transfer in complex biological, social, and artificial systems.
Cortical neurons are typically driven by several thousand synapses. The precise spatiotemporal pattern formed by these inputs can modulate the response of a post-synaptic cell. In this work, we explore how the temporal structure of pre-synaptic inhibitory and excitatory inputs impact the post-synaptic firing of a conductance-based integrate and fire neuron. Both the excitatory and inhibitory input was modeled by renewal gamma processes with varying shape factors for modeling regular and temporally random Poisson activity. We demonstrate that the temporal structure of mutually independent inputs affects the post-synaptic firing, while the strength of the effect depends on the firing rates of both the excitatory and inhibitory inputs. In a second step, we explore the effect of temporal structure of mutually independent inputs on a simple version of Hebbian learning, i.e., hard bound spike-timing-dependent plasticity. We explore both the equilibrium weight distribution and the speed of the transient weight dynamics for different mutually independent gamma processes. We find that both the equilibrium distribution of the synaptic weights and the speed of synaptic changes are modulated by the temporal structure of the input. Finally, we highlight that the sensitivity of both the post-synaptic firing as well as the spike-timing-dependent plasticity on the auto-structure of the input of a neuron could be used to modulate the learning rate of synaptic modification.
In complex networks such as gene networks, traffic systems or brain circuits it is important to understand how long it takes for the different parts of the network to effectively influence one another. In the brain, for example, axonal delays between brain areas can amount to several tens of milliseconds, adding an intrinsic component to any timing-based processing of information. Inferring neural interaction delays is thus needed to interpret the information transfer revealed by any analysis of directed interactions across brain structures. However, a robust estimation of interaction delays from neural activity faces several challenges if modeling assumptions on interaction mechanisms are wrong or cannot be made. Here, we propose a robust estimator for neuronal interaction delays rooted in an information-theoretic framework, which allows a model-free exploration of interactions. In particular, we extend transfer entropy to account for delayed source-target interactions, while crucially retaining the conditioning on the embedded target state at the immediately previous time step. We prove that this particular extension is indeed guaranteed to identify interaction delays between two coupled systems and is the only relevant option in keeping with Wiener’s principle of causality. We demonstrate the performance of our approach in detecting interaction delays on finite data by numerical simulations of stochastic and deterministic processes, as well as on local field potential recordings. We also show the ability of the extended transfer entropy to detect the presence of multiple delays, as well as feedback loops. While evaluated on neuroscience data, we expect the estimator to be useful in other fields dealing with network dynamics.
The neurophysiological changes associated with Alzheimer's Disease (AD) and Mild Cognitive Impairment (MCI) include an increase in low frequency activity, as measured with electroencephalography or magnetoencephalography (MEG). A relevant property of spectral measures is the alpha peak, which corresponds to the dominant alpha rhythm. Here we studied the spatial distribution of MEG resting state alpha peak frequency and amplitude values in a sample of 27 MCI patients and 24 age-matched healthy controls. Power spectra were reconstructed in source space with linearly constrained minimum variance beamformer. Then, 88 Regions of Interest (ROIs) were defined and an alpha peak per ROI and subject was identified. Statistical analyses were performed at every ROI, accounting for age, sex and educational level. Peak frequency was significantly decreased (p < 0.05) in MCIs in many posterior ROIs. The average peak frequency over all ROIs was 9.68 ± 0.71 Hz for controls and 9.05 ± 0.90 Hz for MCIs and the average normalized amplitude was (2.57 ± 0.59)·10(-2) for controls and (2.70 ± 0.49)·10(-2) for MCIs. Age and gender were also found to play a role in the alpha peak, since its frequency was higher in females than in males in posterior ROIs and correlated negatively with age in frontal ROIs. Furthermore, we examined the dependence of peak parameters with hippocampal volume, which is a commonly used marker of early structural AD-related damage. Peak frequency was positively correlated with hippocampal volume in many posterior ROIs. Overall, these findings indicate a pathological alpha slowing in MCI.
Network or graph theory has become a popular tool to represent and analyze large-scale interaction patterns in the brain. To derive a functional network representation from experimentally recorded neural time series one has to identify the structure of the interactions between these time series. In neuroscience, this is often done by pairwise bivariate analysis because a fully multivariate treatment is typically not possible due to limited data and excessive computational cost. Furthermore, a true multivariate analysis would consist of the analysis of the combined effects, including information theoretic synergies and redundancies, of all possible subsets of network components. Since the number of these subsets is the power set of the network components, this leads to a combinatorial explosion (i.e. a problem that is computationally intractable). In contrast, a pairwise bivariate analysis of interactions is typically feasible but introduces the possibility of false detection of spurious interactions between network components, especially due to cascade and common drive effects. These spurious connections in a network representation may introduce a bias to subsequently computed graph theoretical measures (e.g. clustering coefficient or centrality) as these measures depend on the reliability of the graph representation from which they are computed. Strictly speaking, graph theoretical measures are meaningful only if the underlying graph structure can be guaranteed to consist of one type of connections only, i.e. connections in the graph are guaranteed to be non-spurious. ...
The study of neutron-induced reactions is of high relevance in a wide variety of fields, ranging from stellar nucleosynthesis and fundamental nuclear physics to applications of nuclear technology. In nuclear energy, high accuracy neutron data are needed for the development of Generation IV fast reactors and accelerator driven systems, these last aimed specifically at nuclear waste incineration, as well as for research on innovative fuel cycles. In this context, a high luminosity Neutron Time Of Flight facility, n_TOF, is operating at CERN since more than a decade, with the aim of providing new, high accuracy and high resolution neutron cross-sections. Thanks to the features of the neutron beam, a rich experimental program relevant to nuclear technology has been carried out so far. The program will be further expanded in the near future, thanks in particular to a new high-flux experimental area, now under construction.
High precision measurement of the radiative capture cross section of 238U at the n_TOF CERN facility
(2017)
The importance of improving the accuracy on the capture cross-section of 238U has been addressed by the Nuclear Energy Agency, since its uncertainty significantly affects the uncertainties of key design parameters for both fast and thermal nuclear reactors. Within the 7th framework programme ANDES of the European Commission three different measurements have been carried out with the aim of providing the 238U(n,γ) cross-section with an accuracy which varies from 1 to 5%, depending on the energy range. Hereby the final results of the measurement performed at the n_TOF CERN facility in a wide energy range from 1 eV to 700 keV will be presented.
Neutron-induced fission cross sections of 238U and 235U are used as standards in the fast neutron region up to 200 MeV. A high accuracy of the standards is relevant to experimentally determine other neutron reaction cross sections. Therefore, the detection effciency should be corrected by using the angular distribution of the fission fragments (FFAD), which are barely known above 20 MeV. In addition, the angular distribution of the fragments produced in the fission of highly excited and deformed nuclei is an important observable to investigate the nuclear fission process.
In order to measure the FFAD of neutron-induced reactions, a fission detection setup based on parallel-plate avalanche counters (PPACs) has been developed and successfully used at the CERN-n_TOF facility. In this work, we present the preliminary results on the analysis of new 235U(n,f) and 238U(n,f) data in the extended energy range up to 200 MeV compared to the existing experimental data.
The n_TOF facility operates at CERN with the aim of addressing the request of high accuracy nuclear data for advanced nuclear energy systems as well as for nuclear astrophysics. Thanks to the features of the neutron beam, important results have been obtained on neutron induced fission and capture cross sections of U, Pu and minor actinides. Recently the construction of another beam line has started; the new line will be complementary to the first one, allowing to further extend the experimental program foreseen for next measurement campaigns.
The aim of this work is to provide a precise and accurate measurement of the 238U(n,γ) reaction cross section in the energy region from 1 eV to 700 keV. This reaction is of fundamental importance for the design calculations of nuclear reactors, governing the behavior of the reactor core. In particular, fast reactors, which are experiencing a growing interest for their ability to burn radioactive waste, operate in the high energy region of the neutron spectrum. In this energy region most recent evaluations disagree due to inconsistencies in the existing measurements of up to 15%. In addition, the assessment of nuclear data uncertainty performed for innovative reactor systems shows that the uncertainty in the radiative capture cross section of 238U should be further reduced to 1–3% in the energy region from 20 eV to 25 keV. To this purpose, addressed by the Nuclear Energy Agency as a priority nuclear data need, complementary experiments, one at the GELINA and two at the n_TOF facility, were proposed and carried out within the 7th Framework Project ANDES of the European Commission. The results of one of these 238U(n,γ) measurements performed at the n_TOF CERN facility are presented in this work. The γ-ray cascade following the radiative neutron capture has been detected exploiting a setup of two C6D6 liquid scintillators. Resonance parameters obtained from this work are on average in excellent agreement with the ones reported in evaluated libraries. In the unresolved resonance region, this work yields a cross section in agreement with evaluated libraries up to 80 keV, while for higher energies our results are significantly higher.
New results are presented of the 234U neutron-induced fission cross section, obtained with high accuracy in the resonance region by means of two methods using the 235U(n,f) as reference. The recent evaluation of the 235U(n,f) obtained with SAMMY by L. C. Leal et al. (these Proceedings), based on previous n_TOF data [1], has been used to calculate the 234U(n,f) cross section through the 234U/235U ratio, being here compared with the results obtained by using the n_TOF neutron flux.
The 236U isotope plays an important role in nuclear systems, both for future and currently operating ones. The actual knowledge of the capture reaction of this isotope is satisfactory in the thermal region, but it is considered insufficient for Fast Reactor and ADS applications. For this reason the 236U(n, γ) reaction cross-section has been measured for the first time in the whole energy region from thermal energy up to 1 MeV at the n_TOF facility with two different detection systems: an array of C6D6 detectors, employing the total energy deposited method, and a FX1 total absorption calorimeter (TAC), made of 40 BaF2 crystals. The two n_TOF data sets agree with each other within the statistical uncertainty in the Resolved Resonance Region up to 800 eV, while sizable differences (up to ≃ 20%) are found relative to the current evaluated data libraries. Moreover two new resonances have been found in the n_TOF data. In the Unresolved Resonance Region up to 200 keV, the n_TOF results show a reasonable agreement with previous measurements and evaluated data.
The radiative capture cross section of 238U is very important for the developing of new reactor technologies and the safety of existing ones. Here the preliminary results of the 238U(n,γ) cross section measurement performed at n_TOF with C6D6 scintillation detectors are presented, paying particular attention to data reduction and background subtraction.
We have measured the radiative neutron-capture cross section and the total neutron-induced cross section of one of the most important isotopes for the s process, the 25Mg. The measurements have been carried out at the neutron time-of-flight facilities n_TOF at CERN (Switzerland) and GELINA installed at the EC-JRC-IRMM (Belgium). The cross sections as a function of neutron energy have been measured up to approximately 300 keV, covering the energy region of interest to the s process. The data analysis is ongoing and preliminary results show the potential relevance for the s process.
Above 1 MeV of incident neutron energy the fission fragment angular distribution (FFAD) has generally a strong anisotropic behavior due to the combination of the incident orbital momentum and the intrinsic spin of the fissioning nucleus. This effect has to be taken into account for the efficiency estimation of devices used for fission cross section measurements. In addition it bears information on the spin deposition mechanism and on the structure of transitional states. We designed and constructed a detection device, based on Parallel Plate Avalanche Counters (PPAC), for measuring the fission fragment angular distributions of several isotopes, in particular 232Th. The measurement has been performed at n_TOF at CERN taking advantage of the very broad energy spectrum of the neutron beam. Fission events were recognized by back to back detection in coincidence in two position-sensitive detectors surrounding the targets. The detection efficiency, depending mostly on the stopping of fission fragments in backings and electrodes, has been computed with a Geant4 simulation and validated by the comparison to the measured case of 235U below 3 keV where the emission is isotropic. In the case of 232Th, the result is in good agreement with previous data below 10 MeV, with a good reproduction of the structures associated to vibrational states and the opening of second chance fission. In the 14 MeV region our data are much more accurate than previous ones which are broadly scattered.
The neutron sensitivity of the C6D6 detector setup used at n_TOF facility for capture measurements has been studied by means of detailed GEANT4 simulations. A realistic software replica of the entire n_TOF experimental hall, including the neutron beam line, sample, detector supports and the walls of the experimental area has been implemented in the simulations. The simulations have been analyzed in the same manner as experimental data, in particular by applying the Pulse Height Weighting Technique. The simulations have been validated against a measurement of the neutron background performed with a natC sample, showing an excellent agreement above 1 keV. At lower energies, an additional component in the measured natC yield has been discovered, which prevents the use of natC data for neutron background estimates at neutron energies below a few hundred eV. The origin and time structure of the neutron background have been derived from the simulations. Examples of the neutron background for two different samples are demonstrating the important role of accurate simulations of the neutron background in capture cross-section measurements.
The neutron capture cross section of 58Ni was measured at the neutron time of flight facility n_TOF at CERN, from 27 meV to 400 keV neutron energy. Special care has been taken to identify all the possible sources of background, with the so-called neutron background obtained for the first time using high-precision GEANT4 simulations. The energy range up to 122 keV was treated as the resolved resonance region, where 51 resonances were identified and analyzed by a multilevel R-matrix code SAMMY. Above 122 keV the code SESH was used in analyzing the unresolved resonance region of the capture yield. Maxwellian averaged cross sections were calculated in the temperature range of kT = 5 – 100 keV, and their astrophysical implications were investigated.
Cross-frequency coupling (CFC) has been proposed to coordinate neural dynamics across spatial and temporal scales. Despite its potential relevance for understanding healthy and pathological brain function, the standard CFC analysis and physiological interpretation come with fundamental problems. For example, apparent CFC can appear because of spectral correlations due to common non-stationarities that may arise in the total absence of interactions between neural frequency components. To provide a road map towards an improved mechanistic understanding of CFC, we organize the available and potential novel statistical/modeling approaches according to their biophysical interpretability. While we do not provide solutions for all the problems described, we provide a list of practical recommendations to avoid common errors and to enhance the interpretability of CFC analysis.
Background The synchrony hypothesis postulates that precise temporal synchronization of different pools of neurons conveys information that is not contained in their firing rates. The synchrony hypothesis had been supported by experimental findings demonstrating that millisecond precise synchrony of neuronal oscillations across well separated brain regions plays an essential role in visual perception and other higher cognitive tasks [1]. Albeit, more evidence is being accumulated in favour of its role as a binding mechanism of distributed neural responses, the physical and anatomical substrate for such a dynamic and precise synchrony, especially zero-lag even in the presence of non-negligible delays, remains unclear. Here we propose a simple network motif that naturally accounts for zero-lag synchronization for a wide range of temporal delays [3]. We demonstrate that zero-lag synchronization between two distant neurons or neural populations can be achieved by relaying the dynamics via a third mediating single neuron or population. Methods We simulated the dynamics of two Hodgkin-Huxley neurons that interact with each other via an intermediate third neuron. The synaptic coupling was mediated through alpha-functions. Individual temporal delays of the arrival of pre-synaptic potentials were modelled by a gamma distribution. The strength of the synchronization and the phase-difference between each individual pairs were derived by cross-correlation of the membrane potentials. Results In the regular spiking regime the two outer neurons consistently synchronize with zero phase lag irrespective of the initial conditions. This robust zero-lag synchronization naturally arises as a consequence of the relay and redistribution of the dynamics performed by the central neuron. This result is independent on whether the coupling is excitatory or inhibitory and can be maintained for arbitrarily long time delays (see Fig. 1). Conclusion We have presented a simple and extremely robust network motif able to account for the isochronous synchronization of distant neural elements in a natural way. As opposed to other possible mechanisms of neural synchronization, neither inhibitory coupling, gap junctions nor precise tuning of morphological parameters are required to obtain zero-lag synchronized neuronal oscillation.
New neutron cross section measurements of minor actinides have been performed recently in order to reduce the uncertainties in the evaluated data, which is important for the design of advanced nuclear reactors and, in particular, for determining their performance in the transmutation of nuclear waste. We have measured the 241Am(n,γ) cross section at the n_TOF facility between 0.2 eV and 10 keV with a BaF2 Total Absorption Calorimeter, and the analysis of the measurement has been recently concluded. Our results are in reasonable agreement below 20 eV with the ones published by C. Lampoudis et al. in 2013, who reported a 22% larger capture cross section up to 110 eV compared to experimental and evaluated data published before. Our results also indicate that the 241Am(n,γ) cross section is underestimated in the present evaluated libraries between 20 eV and 2 keV by 25%, on average, and up to 35% for certain evaluations and energy ranges.
The accuracy on neutron capture cross section of fissile isotopes must be improved for the design of future nuclear systems such as Gen-IV reactors and Accelerator Driven Systems. The High Priority Request List of the Nuclear Energy Agency, which lists the most important nuclear data requirements, includes also the neutron capture cross sections of fissile isotopes such as 233,235U and 239,241Pu. A specific experimental setup has been used at the CERN n_TOF facility for the measurement of the neutron capture cross section of 235U by a set of micromegas fission detectors placed inside a segmented BaF2 Total Absorption Calorimeter.