Neural Population Decoding in Short-Time Windows

2013 ◽  
pp. 56-63
Author(s):  
Wenhao Zhang ◽  
Si Wu
Keyword(s):  
Time Windows ◽  
Neural Population ◽  
Short Time ◽  
Population Decoding

scholarly journals Peripheral Administration of RF9 Does Not Affect Hypothalamic-PituitaryGonadal Axis in Normal Fed Adult Male Macaque

2020 ◽  
pp. 1-5
Author(s):  
Aalia Batool ◽  
Madiha Wazir ◽  
Rahim Ullah ◽  
Aalia Batool ◽  
Rabia Naz ◽  
...  
Keyword(s):  
Adult Male ◽  
Normal Saline ◽  
Time Windows ◽  
Treated Group ◽  
Plasma Testosterone ◽  
Control Group ◽  
Hpg Axis ◽  
Testosterone Levels ◽  
Physiological Conditions ◽  
Short Time

Stress represses hypothalamic-pituitary-gonadal axis (HPG-axis) but RF9, a synthetic peptide, rescues such repression. To assess the role of RF9 in regulating HPG-axis under normal physiological conditions in higher primates, RF9 was administered to intact adult male rhesus monkeys and response of the HPG-axis was examined by measuring plasma testosterone as an end parameter of the axis. Control group (n=4) received normal saline whereas the treated group (n=4) received RF9. On the first day of experiment, four bolus injections of normal saline (1ml/animal) were administered intravenously at 2-hr interval to the control monkeys. Similarly, on the second day of experiment, treated group received four iv bolus injections of RF9 (0.1mg/kg BW) at 2-hr interval. Serial blood samples were collected at 20 min interval during a 6-hr period which started just after first saline/RF9 injection. Plasma testosterone levels were measured by using a specific EIA. Overall means of plasma testosterone levels and plasma testosterone area under curve (AUC) and overall mean testosterone and mean testosterone AUC in short time windows following each injection of RF9 and saline were comparable between the groups. Our results demonstrate that RF9 has no role in regulating HPG-axis under normal physiological conditions in adult male monkeys.

Parameters of Spike Trains Observed in a Short Time Window

2008 ◽  
Vol 20 (5) ◽  
pp. 1325-1343 ◽  
Author(s):  
Zbyněk Pawlas ◽  
Lev B. Klebanov ◽  
Martin Prokop ◽  
Petr Lansky
Keyword(s):  
Coefficient Of Variation ◽  
Point Processes ◽  
Interspike Interval ◽  
Time Window ◽  
Time Windows ◽  
Time Interval ◽  
Short Time Interval ◽  
Target Neuron ◽  
Short Time Window ◽  
Short Time

We study the estimation of statistical moments of interspike intervals based on observation of spike counts in many independent short time windows. This scenario corresponds to the situation in which a target neuron occurs. It receives information from many neurons and has to respond within a short time interval. The precision of the estimation procedures is examined. As the model for neuronal activity, two examples of stationary point processes are considered: renewal process and doubly stochastic Poisson process. Both moment and maximum likelihood estimators are investigated. Not only the mean but also the coefficient of variation is estimated. In accordance with our expectations, numerical studies confirm that the estimation of mean interspike interval is more reliable than the estimation of coefficient of variation. The error of estimation increases with increasing mean interspike interval, which is equivalent to decreasing the size of window (less events are observed in a window) and with decreasing the number of neurons (lower number of windows).

scholarly journals On Decoding the Responses of a Population of Neurons from Short Time Windows

1999 ◽  
Vol 11 (7) ◽  
pp. 1553-1577 ◽  
Author(s):  
Stefano Panzeri ◽  
Alessandro Treves ◽  
Simon Schultz ◽  
Edmund T. Rolls
Keyword(s):  
Mutual Information ◽  
Information Content ◽  
Computer Simulations ◽  
Time Windows ◽  
Correct Stimulus ◽  
True Value ◽  
Content Index ◽  
Stimulus Identification ◽  
Short Time

The effectiveness of various stimulus identification (decoding) procedures for extracting the information carried by the responses of a population of neurons to a set of repeatedly presented stimuli is studied analytically, in the limit of short time windows. It is shown that in this limit, the entire information content of the responses can sometimes be decoded, and when this is not the case, the lost information is quantified. In particular, the mutual information extracted by taking into account only the most likely stimulus in each trial turns out to be, if not equal, much closer to the true value than that calculated from all the probabilities that each of the possible stimuli in the set was the actual one. The relation between the mutual information extracted by decoding and the percentage of correct stimulus decodings is also derived analytically in the same limit, showing that the metric content index can be estimated reliably from a few cells recorded from brief periods. Computer simulations as well as the activity of real neurons recorded in the primate hippocampus serve to confirm these results and illustrate the utility and limitations of the approach.

scholarly journals Short-time windows of correlation between large-scale functional brain networks predict vigilance intraindividually and interindividually

2012 ◽  
Vol 34 (12) ◽  
pp. 3280-3298 ◽  
Author(s):  
Garth John Thompson ◽  
Matthew Evan Magnuson ◽  
Michael Donelyn Merritt ◽  
Hillary Schwarb ◽  
Wen-Ju Pan ◽  
...  
Keyword(s):  
Large Scale ◽  
Time Windows ◽  
Brain Networks ◽  
Functional Brain ◽  
Functional Brain Networks ◽  
Short Time

scholarly journals Evidence for metastable photo-induced superconductivity in K3C60

2021 ◽  
Author(s):  
M. Budden ◽  
T. Gebert ◽  
M. Buzzi ◽  
G. Jotzu ◽  
E. Wang ◽  
...  
Keyword(s):  
Optical Properties ◽  
High Temperature Superconductivity ◽  
Time Windows ◽  
Far Infrared ◽  
Theoretical Description ◽  
Organic Superconductors ◽  
Small Resistance ◽  
Equilibrium Phases ◽  
Short Time ◽  
Non Equilibrium

AbstractExcitation of high-Tc cuprates and certain organic superconductors with intense far-infrared optical pulses has been shown to create non-equilibrium states with optical properties that are consistent with transient high-temperature superconductivity. These non-equilibrium phases have been generated using femtosecond drives, and have been observed to disappear immediately after excitation, which is evidence of states that lack intrinsic rigidity. Here we make use of a new optical device to drive metallic K3C60 with mid-infrared pulses of tunable duration, ranging between one picosecond and one nanosecond. The same superconducting-like optical properties observed over short time windows for femtosecond excitation are shown here to become metastable under sustained optical driving, with lifetimes in excess of ten nanoseconds. Direct electrical probing, which becomes possible at these timescales, yields a vanishingly small resistance with the same relaxation time as that estimated by terahertz conductivity. We provide a theoretical description of the dynamics after excitation, and justify the observed slow relaxation by considering randomization of the order-parameter phase as the rate-limiting process that determines the decay of the light-induced superconductor.

scholarly journals The dynamic transmission of positional information in stau- mutants during Drosophila embryogenesis

eLife ◽  
2020 ◽  
Vol 9 ◽  
Author(s):  
Zhe Yang ◽  
Hongcun Zhu ◽  
Kakit Kong ◽  
Xiaoxuan Wu ◽  
Jiayi Chen ◽  
...  
Keyword(s):  
Measurement Errors ◽  
Time Windows ◽  
Positional Information ◽  
Intensity Noise ◽  
Wild Type ◽  
Drosophila Embryogenesis ◽  
Self Organized ◽  
Short Time ◽  
Embryo Length ◽  
Drosophila Embryos

It has been suggested that Staufen (Stau) is key in controlling the variability of the posterior boundary of the Hb anterior domain (xHb). However, the mechanism that underlies this control is elusive. Here, we quantified the dynamic 3D expression of segmentation genes in Drosophila embryos. With improved control of measurement errors, we show that the xHb of stau– mutants reproducibly moves posteriorly by 10% of the embryo length (EL) to the wild type (WT) position in the nuclear cycle (nc) 14, and that its variability over short time windows is comparable to that of the WT. Moreover, for stau– mutants, the upstream Bicoid (Bcd) gradients show equivalent relative intensity noise to that of the WT in nc12–nc14, and the downstream Even-skipped (Eve) and cephalic furrow (CF) show the same positional errors as these factors in WT. Our results indicate that threshold-dependent activation and self-organized filtering are not mutually exclusive and could both be implemented in early Drosophila embryogenesis.

scholarly journals Necessary Conditions for Reliable Representation of Asynchronous Spikes Through a Single-layered Feedforward Network

2019 ◽  
Author(s):  
Milad Lankarany
Keyword(s):  
Firing Rate ◽  
Network Model ◽  
Mean Squared Error ◽  
Time Windows ◽  
Model Neuron ◽  
Network Size ◽  
Feedforward Network ◽  
Synaptic Noise ◽  
Reliable Representation ◽  
Short Time

AbstractReliable propagation of firing rate – specifically slow modulation of asynchronous spikes in fairly short time windows [20-500]ms across multiple layers of a feedforward network (FFN) receiving background synaptic noise has proven difficult to capture in spiking models. We, in this paper, explore how information of asynchronous spikes disrupted in the first layer of a typical FFN, and which factors can enable reliable information representation. Our rationale is that the reliable propagation of information across layers of a FFN is likely if that information can be preserved in the first layer of the FFN. In a typical FFN, each layer comprises a certain number (network size) of excitatory neurons – leaky integrate and fire (LIF) model neuron in this paper – receiving correlated input (common stimulus from the upstream layer) plus independent background synaptic noise. We develop a reduced network model of FFN which captures main features of a conventional all-to-all connected FFN. Exploiting the reduced network model, synaptic weights are calculated using a closed-form optimization framework that minimizes the mean squared error between reconstructed stimulus (by spikes of the first layer of FFN) and the original common stimulus. We further explore how representation of asynchronous spikes in a FFN changes with respect to other factors like the network size and the level of background synaptic noise while synaptic weights are optimized for each scenario. We show that not only synaptic weights but also the network size and the level of background synaptic noise are crucial to preserve a reliable representation of asynchronous spikes in the first layer of a FFN. This work sheds light in better understanding of how information of slowly time-varying fluctuations of the firing rate can be transmitted in multi-layered FFNs.

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