scholarly journals The impulse response of S-cone pathways in detection of increments and decrements

2008 ◽  
Vol 25 (3) ◽  
pp. 341-347 ◽  
Author(s):  
KEIZO SHINOMORI ◽  
JOHN S. WERNER
Keyword(s):  
Impulse Response ◽  
Time Course ◽  
Impulse Response Functions ◽  
Detection Thresholds ◽  
Stimulus Interval ◽  
Pulse Detection ◽  
Time To Peak ◽  
Heterochromatic Flicker Photometry ◽  
Maxwellian View ◽  
Cone Adaptation

Impulse response functions (IRFs) were obtained from two-pulse detection thresholds using isoluminant stimuli that produced increments or decrements in S-cone excitation. The pulses were chromatically modulated at constant luminance (based on 18 Hz heterochromatic flicker photometry). Chromatic stimuli were presented as a Gaussian patch (±1 SD = 2.3°) in one of four quadrants around a central fixation cross on a CRT screen. Each of the two pulses (6.67 ms) was separated by an inter-stimulus interval (ISI) from 20 to 360 ms. Chromaticity of the pulses was changed from the equal-energy white of the background to a bluish or yellowish color along individually determined tritan lines (based on color matching under strong S-cone adaptation from a 420 nm background superimposed in Maxwellian view). Chromatic detection thresholds were determined by a four-alternative forced-choice method with staircases for each ISI interleaved in each session. Measurements were repeated in at least four sessions for each observer. IRFs were calculated by varying four parameters of an exponentially-damped sinewave. Both S-cone increment and decrement IRFs are characterized by a single excitatory phase and a much longer time course compared with IRFs derived for luminance modulation using the same apparatus and observers. S-cone increment IRFs are faster than S-cone decrement IRFs; the time to peak amplitude of S-cone increment and decrement IRFs is 50–70 and 100–120 ms, respectively. These results were used to derive the temporal contrast sensitivity for human observers of putative ON- and OFF-channels carrying signals from S-cones.

scholarly journals Spectral Analysis of Dynamic PET Studies

1993 ◽  
Vol 13 (1) ◽  
pp. 15-23 ◽  
Author(s):  
Vincent J. Cunningham ◽  
Terry Jones
Keyword(s):  
Impulse Response ◽  
Time Course ◽  
Arterial Input Function ◽  
Impulse Response Function ◽  
Impulse Response Functions ◽  
Dynamic Pet ◽  
Computer Algorithms ◽  
Arterial Blood ◽  
Unit Impulse ◽  
Unit Impulse Response

We describe a new technique for the analysis of dynamic positron emission tomography (PET) studies in humans, where data consist of the time courses of label in tissue regions of interest and in arterial blood, following the administration of radiolabeled tracers. The technique produces a simple spectrum of the kinetic components which relate the tissue's response to the blood activity curve. From this summary of the kinetic components, the tissue's unit impulse response can be derived. The convolution of the arterial input function with the derived unit impulse response function gives the curve of best fit to the observed tissue data. The analysis makes no a priori assumptions regarding the number of compartments or components required to describe the time course of label in the tissue. Rather, it is based on a general linear model, presented here in a formulation compatible with its solution using standard computer algorithms. Its application is illustrated with reference to cerebral blood flow, glucose utilization, and ligand binding. The interpretation of the spectra, and of the tissue unit impulse response functions, are discussed in terms of vascular components, unidirectional clearance of tracer by the tissue, and reversible and irreversible phenomena. The significance of the number of components which can be identified within a given datum set is also discussed. The technique facilitates the interpretation of dynamic PET data and simplifies comparisons between regions and between subjects.

Slow Wave Activity Related to Working Memory Maintenance in the N-Back Task

2016 ◽  
Vol 30 (4) ◽  
pp. 141-154 ◽  
Author(s):  
Kira Bailey ◽  
Gregory Mlynarczyk ◽  
Robert West
Keyword(s):  
Working Memory ◽  
Slow Wave ◽  
Time Course ◽  
Relevant Information ◽  
Wave Activity ◽  
Slow Wave Activity ◽  
Response Accuracy ◽  
Functional Neuroanatomy ◽  
Stimulus Interval ◽  
Back Task

Abstract. Working memory supports our ability to maintain goal-relevant information that guides cognition in the face of distraction or competing tasks. The N-back task has been widely used in cognitive neuroscience to examine the functional neuroanatomy of working memory. Fewer studies have capitalized on the temporal resolution of event-related brain potentials (ERPs) to examine the time course of neural activity in the N-back task. The primary goal of the current study was to characterize slow wave activity observed in the response-to-stimulus interval in the N-back task that may be related to maintenance of information between trials in the task. In three experiments, we examined the effects of N-back load, interference, and response accuracy on the amplitude of the P3b following stimulus onset and slow wave activity elicited in the response-to-stimulus interval. Consistent with previous research, the amplitude of the P3b decreased as N-back load increased. Slow wave activity over the frontal and posterior regions of the scalp was sensitive to N-back load and was insensitive to interference or response accuracy. Together these findings lead to the suggestion that slow wave activity observed in the response-to-stimulus interval is related to the maintenance of information between trials in the 1-back task.

Impulse-response functions and anthropogenic CO2

1995 ◽  
Vol 22 (4) ◽  
pp. 413-416 ◽  
Author(s):  
Francesco N. Tubiello ◽  
Michael Oppenheimer
Keyword(s):  
Impulse Response ◽  
Impulse Response Functions ◽  
Response Functions ◽  
Anthropogenic Co2

scholarly journals Sodium and calcium currents in dispersed mammalian septal neurons.

1991 ◽  
Vol 97 (2) ◽  
pp. 303-320 ◽  
Author(s):  
A Castellano ◽  
J López-Barneo
Keyword(s):  
Time Constant ◽  
Time Course ◽  
Calcium Currents ◽  
Closing Time ◽  
Patch Clamp Technique ◽  
Average Value ◽  
Time To Peak ◽  
Time Courses ◽  
Fast Activation ◽  
Septal Neurons

Voltage-gated Na+ and Ca2+ conductances of freshly dissociated septal neurons were studied in the whole-cell configuration of the patch-clamp technique. All cells exhibited a large Na+ current with characteristic fast activation and inactivation time courses. Half-time to peak current at -20 mV was 0.44 +/- 0.18 ms and maximal activation of Na+ conductance occurred at 0 mV or more positive membrane potentials. The average value was 91 +/- 32 nS (approximately 11 mS cm-2). At all membrane voltages inactivation was well fitted by a single exponential that had a time constant of 0.44 +/- 0.09 ms at 0 mV. Recovery from inactivation was complete in approximately 900 ms at -80 mV but in only 50 ms at -120 mV. The decay of Na+ tail currents had a single time constant that at -80 mV was faster than 100 microseconds. Depolarization of septal neurons also elicited a Ca2+ current that peaked in approximately 6-8 ms. Maximal peak Ca2+ current was obtained at 20 mV, and with 10 mM external Ca2+ the amplitude was 0.35 +/- 0.22 nA. During a maintained depolarization this current partially inactivated in the course of 200-300 ms. The Ca2+ current was due to the activity of two types of conductances with different deactivation kinetics. At -80 mV the closing time constants of slow (SD) and fast (FD) deactivating channels were, respectively, 1.99 +/- 0.2 and 0.11 +/- 0.03 ms (25 degrees C). The two kinds of channels also differed in their activation voltage, inactivation time course, slope of the conductance-voltage curve, and resistance to intracellular dialysis. The proportion of SD and FD channels varied from cell to cell, which may explain the differential electrophysiological responses of intracellularly recorded septal neurons.

IMPROVING EXTRACTION OF IMPULSE RESPONSE FUNCTIONS USING STATIONARY WAVELET SHRINKAGE IN TERAHERTZ REFLECTION IMAGING

2010 ◽  
Vol 09 (04) ◽  
pp. 387-394 ◽  
Author(s):  
YANG CHEN ◽  
YIWEN SUN ◽  
EMMA PICKWELL-MACPHERSON
Keyword(s):  
Experimental Data ◽  
Impulse Response ◽  
Response Function ◽  
Impulse Response Function ◽  
Terahertz Imaging ◽  
Impulse Response Functions ◽  
Response Functions ◽  
Inverse Filtering ◽  
Wavelet Shrinkage ◽  
Gaussian Filtering

In terahertz imaging, deconvolution is often performed to extract the impulse response function of the sample of interest. The inverse filtering process amplifies the noise and in this paper we investigate how we can suppress the noise without over-smoothing and losing useful information. We propose a robust deconvolution process utilizing stationary wavelet shrinkage theory which shows significant improvement over other popular methods such as double Gaussian filtering. We demonstrate the success of our approach on experimental data of water and isopropanol.

A Comparison of Approaches to Select the Informativeness of Priors in BVARs

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Jan Prüser ◽  
Christoph Hanck
Keyword(s):  
Impulse Response ◽  
Prior Information ◽  
Hierarchical Modeling ◽  
Small Samples ◽  
Model Parameters ◽  
Impulse Response Functions ◽  
Response Functions ◽  
Vector Autoregressions ◽  
The Rich ◽  
Bayesian Vars

Abstract Vector autoregressions (VARs) are richly parameterized time series models that can capture complex dynamic interrelationships among macroeconomic variables. However, in small samples the rich parametrization of VAR models may come at the cost of overfitting the data, possibly leading to imprecise inference for key quantities of interest such as impulse response functions (IRFs). Bayesian VARs (BVARs) can use prior information to shrink the model parameters, potentially avoiding such overfitting. We provide a simulation study to compare, in terms of the frequentist properties of the estimates of the IRFs, useful strategies to select the informativeness of the prior. The study reveals that prior information may help to obtain more precise estimates of impulse response functions than classical OLS-estimated VARs and more accurate coverage rates of error bands in small samples. Strategies based on selecting the prior hyperparameters of the BVAR building on empirical or hierarchical modeling perform particularly well.

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