Characterization of reliability of spike timing in spinal interneurons during oscillating inputs

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Real-time identification, tracking, and sensing of single living cells have the potential to transform cellular biology by enabling unprecedented insight into cellular behaviour and interactions, with applications in diagnostics and treatment of complex diseases such as cancer. One promising approach is near-field radio-frequency identification (RFID), particularly in the UHF band (300 MHz - 3 GHz), where identification ranges on the order of one wavelength can be achieved. An RFID system consists of a tag

In some forms of postdictive phenomena, later events influence the perception of earlier ones, suggesting that conscious perception may be preceded by extended periods of unconscious processing. An example is the Sequential Metacontrast (SQM) paradigm, in which vernier offsets are unconsciously integrated over several hundred milliseconds before conscious perception. Obviously, the integrated percept can only emerge after each individual element in the stream has been processed. Thus, the SQM provides a uni

Kinetic effects of bulk and fast particles in tokamaks can significantly impact the stability predictions of Magnetohydrodynamic (MHD) modes. Hybrid kinetic-MHD models are typically used to estimate these effects. Many such existing codes compute the kinetic effects by solving a reduced drift-kinetic or gyrokinetic equation semi-analytically, which often involves approximations limiting the type of orbits that can be accurately reproduced. Others solve particle orbits as a time evolution problem, requiring

Abstract A recurrent neural network fitted to large electrophysiological datasets may help us understand the chain of cortical information transmission. In particular, successful network reconstruction methods should enable a model to predict the response to optogenetic perturbations. We test recurrent neural networks (RNNs) fitted to electrophysiological datasets on unseen optogenetic interventions, and measure that generic RNNs used predominantly in the field generalize poorly on these perturbations. Our

Accumulating evidence suggests that the brain continuously monitors the predictability of rapidly evolving sound sequences, even when they are not behaviorally relevant. An increasing body of empirical evidence links sustained tonic M/EEG activity to evidence accumulation and tracking the predictability, or inferred precision, of the auditory stimulus. However, it remains unclear whether, and how, this process depends on auditory contextual memory. We investigated how the history of sound sequences influenc

The observation of a wide peaking structure in the (Formula presented) mass spectrum is reported using proton-proton collision data collected by the LHCb detector at center-of-mass energies of 7, 8, and 13 TeV, corresponding to a total integrated luminosity of (Formula presented). The statistical significance over the background-only hypothesis exceeds seven standard deviations. The width of the observed structure is larger than the expectation from a single-peak hypothesis, and is well described by an effe

The functional organization of the human spinal cord has primarily been derived from clinical observations and invasive electrophysiological studies. Recent methodological advances opened the possibility of studying the neuronal activity of the spinal cord in humans using noninvasive functional magnetic resonance imaging (fMRI). Here, we took advantage of fMRI to map the patterns of activity elicited by muscle‐specific proprioceptive information along the whole cervical cord. We quantified the fMRI signals

We propose a mathematical model based on multivariate Hawkes processes for the activity of (natural) neural networks, where the excitation function of each neuron is modelled as a 2nd order causal exponential spline. Then, we estimate the parameters of the multivariate Hawkes process given a realization using maximum likelihood estimation, which is numerically implemented using an adaptation of the Polyatomic Frank-Wolfe algorithm, selected for its sparsity-promoting properties. Finally, we test our algorit

Stochastic channel gating is the major source of intrinsic neuronal noise whose functional consequences at the microcircuit- and network-levels have been only partly explored. A systematic study of this channel noise in large ensembles of biophysically det ...

Behavioral and brain responses to identical stimuli can vary with experimental and task parameters, including the context of stimulus presentation or attention. More surprisingly, computational models suggest that noise-related random fluctuations in brain responses to stimuli would alone be sufficient to engender perceptual differences between physically identical stimuli. In two experiments combining psychophysics and EEG in healthy humans, we investigated brain mechanisms whereby identical stimuli are (e

Functional connectivity analysis of fMRI data can reveal synchronized activity between anatomically distinct brain regions. Here, we exploit the characteristic connectivity graphs of task and resting epochs to perform classification between these conditions. Our approach is based on ensembles of decision trees, which combine powerful discriminative ability with interpretability of results. This makes it possible to extract discriminative graphs that represent a subset of the connections that distinguish bes

We demonstrate that single-variable integrate-and-fire models can quantitatively capture the dynamics of a physiologically-detailed model for fast-spiking cortical neurons. Through a systematic set of approximations, we reduce the conductance based model to two variants of integrate-and-fire models. In the first variant (non-linear integrate-and-fire model), parameters depend on the instantaneous membrane potential whereas in the second variant, they depend on the time elapsed since the last spike (Spike Re

The equilibrium rheological properties of a range of isotropic exfoliated and intercalated hyperbranched polymer (HBP)/montmorillonite (MMT) clay nanocomposites have been investigated using low strain oscillating shear measurements at temperatures above the glass transition temperature of the HBP. Predominantly exfoliated nanocomposites showed a sharp increase in shear viscosity at about 0.8 wt % MMT, associated with a transition from Newtonian to solid-like behavior, which was characterized in terms of a l

Background: For the investigation of the molecular mechanisms involved in neurite outgrowth and differentiation, accurate and reproducible segmentation and quantification of neuronal processes are a prerequisite. To facilitate this task, we developed a semiautomatic neurite tracing technique. This article describes the design and validation of the technique. Methods: The technique was compared to fully manual delineation. Four observers repeatedly traced selected neurites in 20 fluorescence microscopy image

After the recent development of the theory of nonlinear dynamical systems and deterministic chaos and the introduction of one, in theory, simple method for computing the phase space, many researchers started to analyze electroencephalographic (EEG) signals in terms of nonlinear dynamics, with the belief that new information not accessible by linear analysis could be obtained. However, after an initial enthusiasm, many results obtained with short-length and noisy data have come under question. After a short

What is the meaning' of a single spike? Spike-triggered averaging (reverse correlations') yields the typical input just before a spike. Similarly, cross-correlations describe the probability of firing an output spike given (one additional) presynaptic input spike. In this paper we analytically calculate reverse and cross-correlations for a spiking neuron model with escape noise. The influence of neuronal parameters (such as the membrane time constant, the noise level, and the mean firing rate) on the form

A correlation-based (

Hebbian'') learning rule at the spike level is formulated, mathematically analyzed, and compared with learning in a firing-rate description. As for spike coding, we take advantage of a

learning window'' that describes the effect of timing of pre- and postsynaptic spikes on synaptic weights. A differential equation for the learning dynamics is derived under the assumption that the time scales of learning and spiking dynamics can be separated. Formation of structured synapses is analy

The a.c. self-field loss in Bi(2223)Ag sheathed tapes with different number of filaments has been measured between 59 and 2500 Hz by means of a dual lock-in amplifier. Due to the wide frequency range of the measurements we have been able to dissociate quantitatively the different self-field loss contributions: hysteretic, eddy current and resistive loss (near Ic). This is an important advantage compared to single frequency measurements where such loss dissociation is only qualitative. The hysteresis losses

The authors present an analysis in the frequency domain of lightning electromagnetic fields making use of a computer code developed by the authors. The analysis is made for different distances from the lightning channel, for two different current waveshapes corresponding to the first and the subsequent negative return stroke, and evidencing the contribution of the various terms (static, induction and radiation) to the total field. The calculated frequency spectra match satisfactorily with the average spectr

Characterization of reliability of spike timing in spinal interneurons during oscillating inputs

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