ABSTRACT. Rapidclimate changes during the last glacialperiodwere first observed in ice-core records (Dansgaard and others, 1982). These shifts between interstadials, called Dansgaard^Oeschger (D-O) events, and stadials or deep glaciation... more
ABSTRACT. Rapidclimate changes during the last glacialperiodwere first observed in ice-core records (Dansgaard and others, 1982). These shifts between interstadials, called Dansgaard^Oeschger (D-O) events, and stadials or deep glaciation were later seen in Atlantic sediment records (Bond and others, 1993), pointing to the ocean circulation as a strong component in the dynamics of these shifts (Wright andStocker,1991).The interstadial states are observed to have a characteristic ` ̀ sawtooth’ ’ shape, indicating a gradual drift of the stable interstadial state toward the stable stadial state. In order to contrast the two climate states, we have separated the d18O signal from the Greenland Icecore Project ice core into periods corresponding to the two states. The climate variability in the two differ-ent climatic states is different (Johnsen andothers,1997).We find that the standarddeviation is significantly larger in the stadial than in the interstadial state. Both states are found t...
s (Talks) 5 Adeline Samson. PARAMETER ESTIMATION IN THE STOCHASTIC MORRIS-LECAR NEURONAL MODEL . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 Alexander Schnurr. AN ORDINAL PATTERN APPROACH TO DETECT AND TO... more
s (Talks) 5 Adeline Samson. PARAMETER ESTIMATION IN THE STOCHASTIC MORRIS-LECAR NEURONAL MODEL . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 Alexander Schnurr. AN ORDINAL PATTERN APPROACH TO DETECT AND TO MODEL DEPENDENCE STRUCTURES BETWEEN FINANCIAL TIME SERIES . . . . . . . . . . . . 7 Benedikt Funke. ADAPTIVE NADARAYA-WATSON LIKE ESTIMATORS FOR THE ESTIMATION OF THE DRIFT IN A JUMP DIFFUSION MODEL . . . . . . . . . . . . . . . . . . 8 Catherine Larédo EQUIVALENCE FOR NON PARAMETRIC DRIFT ESTIMATION OF A DIFFUSION PROCESS AND ITS EULER SCHEME . . . . . . . . . . . . . . . . . . . . . . . 9 Christian Schmidt. LIMIT THEOREMS FOR NON-DEGENERATE U-STATISTICS OF CONTINUOUS SEMIMARTINGALES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10 Dominique Dehay. PARAMETRIC AND NONPARAMETRIC ESTIMATION PROBLEMS FOR SOME TIME-PERIODIC-DRIFT LANGEVIN TYPE STOCHASTIC DIFFERENTIAL EQUATION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ....
In the last decade, Hawkes processes have received a lot of attention as good models for functional connectivity in neural spiking networks. In this paper we consider a variant of this process, the Age Dependent Hawkes process, which... more
In the last decade, Hawkes processes have received a lot of attention as good models for functional connectivity in neural spiking networks. In this paper we consider a variant of this process, the Age Dependent Hawkes process, which incorporates individual post-jump behaviour into the framework of the usual Hawkes model. This allows to model recovery properties such as refractory periods, where the effects of the network are momentarily being suppressed or altered. We show how classical stability results for Hawkes processes can be improved by introducing age into the system. In particular, we neither need to a priori bound the intensities nor to impose any conditions on the Lipschitz constants. When the interactions between neurons are of mean field type, we study large network limits and establish the propagation of chaos property of the system.
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One of the last pristine marine soundscapes, the Arctic, is exposed to increasing anthropogenic activities due to climate-induced decrease in sea ice coverage. In this study, we combined movement and behavioral data from animal-borne tags... more
One of the last pristine marine soundscapes, the Arctic, is exposed to increasing anthropogenic activities due to climate-induced decrease in sea ice coverage. In this study, we combined movement and behavioral data from animal-borne tags in a controlled sound exposure study to describe the reactions of narwhals, Monodon monoceros, to airgun pulses and ship noise. Sixteen narwhals were live captured and instrumented with satellite tags and Acousonde acoustic-behavioral recorders, and 11 of them were exposed to airgun pulses and vessel sounds. The sound exposure levels (SELs) of pulses from a small airgun (3.4 L) used in 2017 and a larger one (17.0 L) used in 2018 were measured using drifting recorders. The experiment was divided into trials with airgun and ship-noise exposure, intertrials with only ship-noise, and pre- and postexposure periods. Both trials and intertrials lasted ∼4 h on average per individual. Depending on the location of the whales, the number of separate exposures...
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The ages of three species of cetaceans were estimated by counting the growth layer groups (GLG) and measuring the aspartic acid racemization rate (kAsp) by what is referred to as the Aspartic Acid Racemization (AAR) technique. Data on... more
The ages of three species of cetaceans were estimated by counting the growth layer groups (GLG) and measuring the aspartic acid racemization rate (kAsp) by what is referred to as the Aspartic Acid Racemization (AAR) technique. Data on kAsp and the D/L ratio of aspartic acid at birth [(D/L)0] in North Atlantic common minke whales (Balaenoptera acutorostrata) are presented along with data on fin whales (B. physalus) and harbour porpoises (Phocoena phocoena) already published by Nielsen et al. (2012). The kAsp specific for minke whales was 1.40 x 10-3 yr-1 (SE ± 0.00005) and the (D/L)0 was 0.0194 (SE ± 0.0012). The correlation of GLG age and D/L ratio for all three species was highly significant; however, the correlation coefficient varied greatly (fin whales: R2 = 0.59, p <0.0001; minke whales: R2=0.96, P <0.0001; harbour porpoises: R2=0.36, P <0.0001). Asymptotic body length for all three species was estimated by a von Bertalanffy growth model on both the GLG and AAR techn...
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We consider a classical space-clamped Hodgkin-Huxley model neuron stimulated by synaptic excitation and inhibition with conductances represented by Ornstein-Uhlenbeck processes. Using numerical solutions of the stochastic model system... more
We consider a classical space-clamped Hodgkin-Huxley model neuron stimulated by synaptic excitation and inhibition with conductances represented by Ornstein-Uhlenbeck processes. Using numerical solutions of the stochastic model system obtained by an Euler method, it is found that with excitation only, there is a critical value of the steady-state excitatory conductance for repetitive spiking without noise, and for values of the conductance near the critical value, small noise has a powerfully inhibitory effect. For a given level of inhibition, there is also a critical value of the steady-state excitatory conductance for repetitive firing, and it is demonstrated that noise in either the excitatory or inhibitory processes or both can powerfully inhibit spiking. Furthermore, near the critical value, inverse stochastic resonance was observed when noise was present only in the inhibitory input process. The system of deterministic differential equations for the approximate first- and seco...
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We present cointegration analysis as a method to infer the network structure of a linearly phase coupled oscillating system. By defining a class of oscillating systems with interacting phases, we derive a data generating process where we... more
We present cointegration analysis as a method to infer the network structure of a linearly phase coupled oscillating system. By defining a class of oscillating systems with interacting phases, we derive a data generating process where we can specify the coupling structure of a network that resembles biological processes. In particular we study a network of Winfree oscillators, for which we present a statistical analysis of various simulated networks, where we conclude on the coupling structure: the direction of feedback in the phase processes and proportional coupling strength between individual components of the system. We show that we can correctly classify the network structure for such a system by cointegration analysis, for various types of coupling, including uni-/bi-directional and all-to-all coupling. Finally, we analyze a set of EEG recordings and discuss the current applicability of cointegration analysis in the field of neuroscience.
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A fundamental question concerning representation of the visual world in our brain is how a cortical cell responds when presented with more than a single stimulus. We find supportive evidence that most cells presented with a pair of... more
A fundamental question concerning representation of the visual world in our brain is how a cortical cell responds when presented with more than a single stimulus. We find supportive evidence that most cells presented with a pair of stimuli respond predominantly to one stimulus at a time, rather than a weighted average response. Traditionally, the firing rate is assumed to be a weighted average of the firing rates to the individual stimuli (response-averaging model) (Bundesen et al., 2005). Here, we also evaluate a probability-mixing model (Bundesen et al., 2005), where neurons temporally multiplex the responses to the individual stimuli. This provides a mechanism by which the representational identity of multiple stimuli in complex visual scenes can be maintained despite the large receptive fields in higher extrastriate visual cortex in primates. We compare the two models through analysis of data from single cells in the middle temporal visual area (MT) of rhesus monkeys when presen...
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A fundamental question concerning the way the visual world is represented in our brain is how a cortical cell responds when its classical receptive field contains a plurality of stimuli. Two opposing models have been proposed. In the... more
A fundamental question concerning the way the visual world is represented in our brain is how a cortical cell responds when its classical receptive field contains a plurality of stimuli. Two opposing models have been proposed. In the response-averaging model, the neuron responds with a weighted average of all individual stimuli. By contrast, in the probability-mixing model, the cell responds to a plurality of stimuli as if only one of the stimuli were present. Here we apply the probability-mixing and the response-averaging model to leaky integrate-and-fire neurons, to describe neuronal behavior based on observed spike trains. We first estimate the parameters of either model using numerical methods, and then test which model is most likely to have generated the observed data. Results show that the parameters can be successfully estimated and the two models are distinguishable using model selection.
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Selenomethionine (SeMet) is an important organic nutritional source of Se, but the uptake and metabolism of SeMet are poorly characterised in humans. Dynamic gamma camera images of the abdominal region were acquired from eight healthy... more
Selenomethionine (SeMet) is an important organic nutritional source of Se, but the uptake and metabolism of SeMet are poorly characterised in humans. Dynamic gamma camera images of the abdominal region were acquired from eight healthy young men after the ingestion of radioactive75Se-l-SeMet (75Se-SeMet). Scanning started simultaneously to the ingestion of75Se-SeMet and lasted 120 min. We generated time-activity curves from two-dimensional regions of interest in the stomach, small intestine and liver. During scanning, blood samples were collected at 10-min intervals to generate plasma time-activity curves. A four-compartment model, augmented with a delay between the liver and plasma, was fitted to individual participants’ data. The mean rate constant for75Se-SeMet transport was 2·63 h–1from the stomach to the small intestine, 13·2 h–1from the small intestine to the liver, 0·261 h–1from the liver to the plasma and 0·267 h–1from the stomach to the plasma. The delay in the liver was 0·7...
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Research Interests: Neuroscience, Electrophysiology, Biology, Medicine, Multidisciplinary, and 15 moreStochastic processes, Computer Simulation, Animals, Spinal Cord, Research article, Neurons, PLoS one, Motor System, SYNAPSES, Action potential, Membrane Potential, Action Potentials, Electric Conductivity, Motor activity, and Motor Neurons
When recording the membrane potential, V, of a neuron it is desirable to be able to extract the synaptic input. Critically, the synaptic input is stochastic and nonreproducible so one is therefore often restricted to single-trial data.... more
When recording the membrane potential, V, of a neuron it is desirable to be able to extract the synaptic input. Critically, the synaptic input is stochastic and nonreproducible so one is therefore often restricted to single-trial data. Here, we introduce means of estimating the inhibition and excitation and their confidence limits from single sweep trials. The estimates are based on the mean membrane potential, V̄, and the membrane time constant, τ. The time constant provides the total conductance ( G = capacitance/τ) and is extracted from the autocorrelation of V. The synaptic conductances can then be inferred from V̄ when approximating the neuron as a single compartment. We further employ a stochastic model to establish limits of confidence. The method is verified on models and experimental data, where the synaptic input is manipulated pharmacologically or estimated by an alternative method. The method gives best results if the synaptic input is large compared with other conductan...
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Research Interests: Engineering, Computer Science, Physics, Computational Neuroscience, Medicine, and 15 moreSpike train analysis, Computer Simulation, Diffusion, Animals, Spinal Cord, Article, Computational, Diffusion Coefficient, Constant Time Delay, Membrane Potential, Action Potentials, Experimental Data, Motor Neurons, Psychology and Cognitive Sciences, and Medical and Health Sciences
Research Interests: Algorithms, Epidemiology, Psychometrics, Environmental Monitoring, Air pollution, and 15 moreMacular Degeneration, Denmark, Humans, Female, Male, Regression Analysis, Middle Aged, Longitudinal Studies, Myocardial Infarction, Adult, Public health systems and services research, Age Factors, Environmental Exposure, Air Pollutants, and Interferon Alpha
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Neuronal response latency is usually vaguely defined as the delay between the stimulus onset and the beginning of the response. It contains important information for the understanding of the temporal code. For this reason, the detection... more
Neuronal response latency is usually vaguely defined as the delay between the stimulus onset and the beginning of the response. It contains important information for the understanding of the temporal code. For this reason, the detection of the response latency has been extensively studied in the last twenty years, yielding different estimation methods. They can be divided into two classes, one of them including methods based on detecting an intensity change in the firing rate profile after the stimulus onset and the other containing methods based on detection of spikes evoked by the stimulation using interspike intervals and spike times. The aim of this paper is to present a review of the main techniques proposed in both classes, highlighting their advantages and shortcomings.