scholarly journals A Spatiotemporal White Noise Analysis of Photoreceptor Responses to UV and Green Light in the Dragonfly Median Ocellus

2005 ◽  
Vol 126 (5) ◽  
pp. 481-497 ◽  
Author(s):  
Joshua van Kleef ◽  
Andrew Charles James ◽  
Gert Stange
Keyword(s):  
Linear Response ◽  
Noise Analysis ◽  
Receptive Fields ◽  
Green Light ◽  
Second Order ◽  
Ambient Temperatures ◽  
Kernel Analysis ◽  
Green Response ◽  
Log Normal ◽  
Nonlinear Components

Adult dragonflies augment their compound eyes with three simple eyes known as the dorsal ocelli. While the ocellar system is known to mediate stabilizing head reflexes during flight, the ability of the ocellar retina to dynamically resolve the environment is unknown. For the first time, we directly measured the angular sensitivities of the photoreceptors of the dragonfly median (middle) ocellus. We performed a second-order Wiener Kernel analysis of intracellular recordings of light-adapted photoreceptors. These were stimulated with one-dimensional horizontal or vertical patterns of concurrent UV and green light with different contrast levels and at different ambient temperatures. The photoreceptors were found to have anisotropic receptive fields with vertical and horizontal acceptance angles of 15° and 28°, respectively. The first-order (linear) temporal kernels contained significant undershoots whose amplitudes are invariant under changes in the contrast of the stimulus but significantly reduced at higher temperatures. The second-order kernels showed evidence of two distinct nonlinear components: a fast acting self-facilitation, which is dominant in the UV, followed by delayed self- and cross-inhibition of UV and green light responses. No facilitatory interactions between the UV and green light were found, indicating that facilitation of the green and UV responses occurs in isolated compartments. Inhibition between UV and green stimuli was present, indicating that inhibition occurs at a common point in the UV and green response pathways. We present a nonlinear cascade model (NLN) with initial stages consisting of separate UV and green pathways. Each pathway contains a fast facilitating nonlinearity coupled to a linear response. The linear response is described by an extended log-normal model, accounting for the phasic component. The final nonlinearity is composed of self-inhibition in the UV and green pathways and inhibition between these pathways. The model can largely predict the response of the photoreceptors to UV and green light.

scholarly journals Applicability of White-Noise Techniques to Analyzing Motion Responses

2010 ◽  
Vol 103 (5) ◽  
pp. 2642-2651 ◽  
Author(s):  
Joshua P. van Kleef ◽  
Gert Stange ◽  
Michael R. Ibbotson
Keyword(s):  
White Noise ◽  
Noise Analysis ◽  
Receptive Fields ◽  
Spatial Location ◽  
Second Order ◽  
Motion Processing ◽  
White Noise Analysis ◽  
Visual Neurons ◽  
Gaze Stabilization ◽  
Spatiotemporal Receptive Fields

Motion processing in visual neurons is often understood in terms of how they integrate light stimuli in space and time. These integrative properties, known as the spatiotemporal receptive fields (STRFs), are sometimes obtained using white-noise techniques where a continuous random contrast sequence is delivered to each spatial location within the cell's field of view. In contrast, motion stimuli such as moving bars are usually presented intermittently. Here we compare the STRF prediction of a neuron's response to a moving bar with the measured response in second-order interneurons (L-neurons) of dragonfly ocelli (simple eyes). These low-latency neurons transmit sudden changes in intensity and motion information to mediate flight and gaze stabilization reflexes. A white-noise analysis is made of the responses of L-neurons to random bar stimuli delivered either every frame (densely) or intermittently (sparsely) with a temporal sequence matched to the bar motion stimulus. Linear STRFs estimated using the sparse stimulus were significantly better at predicting the responses to moving bars than the STRFs estimated using a traditional dense white-noise stimulus, even when second-order nonlinear terms were added. Our results strongly suggest that visual adaptation significantly modifies the linear STRF properties of L-neurons in dragonfly ocelli during dense white-noise stimulation. We discuss the ability to predict the responses of visual neurons to arbitrary stimuli based on white-noise analysis. We also discuss the likely functional advantages that adaptive receptive field structures provide for stabilizing attitude during hover and forward flight in dragonflies.

Response dynamics and receptive-field organization of catfish amacrine cells

1992 ◽  
Vol 67 (2) ◽  
pp. 430-442 ◽  
Author(s):  
H. M. Sakai ◽  
K. Naka
Keyword(s):  
Receptive Field ◽  
White Noise ◽  
Amacrine Cells ◽  
Second Order ◽  
Response Dynamics ◽  
Field Center ◽  
Mean Luminance ◽  
Nonlinear Components ◽  
Receptive Field Center ◽  
Dc Potentials

1. We have applied Wiener analysis to a study of response dynamics of N (sustained) and C (transient) amacrine cells. Stimuli were a spot and an annulus of light, the luminance of which was modulated by two independent white-noise signals. First- and second-order Wiener kernels were computed for each spot and annulus input. The analysis allowed us to separate a modulation response into its linear and nonlinear components, and into responses generated by a receptive-field center and its surround. 2. Organization of the receptive field of N amacrine cells consists of both linear and nonlinear components. The receptive field of linear components was center-surround concentric and opposite in polarity, whereas that of second-order nonlinear components was monotonic. 3. In NA (center-depolarizing) amacrine cells, the membrane DC potentials brought about by the mean luminance of a white-noise spot or a steady spot were depolarizations, whereas those brought about by the mean luminance of a white-noise annulus or a steady annulus were hyperpolarizations. In NB (center-hyperpolarizing) amacrine cells, this relationship was reversed. If both receptive-field center and surround were stimulated by a spot and annulus, membrane DC potentials became close to the dark level and the amplitude of modulation responses became larger. 4. The linear responses of a receptive-field center of an N amacrine cell, measured in terms of the first-order Wiener kernel, were facilitated if the surround was stimulated simultaneously. The amplitude of the kernel became larger, and its peak response time became shorter. The same facilitation occurred in the linear responses of a receptive-field surround if the center was stimulated simultaneously. 5. The second-order nonlinear responses were not usually generated in N amacrine cells if the stimulus was either a white-noise spot or a white-noise annulus alone. Significant second-order nonlinearity appeared if the other region of the receptive field was also stimulated. 6. Membrane DC potentials of C amacrine cells remained at the dark level with either a white-noise spot or a white-noise annulus. The cell responded only to modulations. 7. The major characteristics of center and surround responses of C amacrine cells could be approximated by second-order Wiener kernels of the same structure. The receptive field of second-order nonlinear components of C amacrine cells was monotonic.(ABSTRACT TRUNCATED AT 400 WORDS)

Sensory processing in a thermal afferent pathway

1985 ◽  
Vol 53 (2) ◽  
pp. 429-434 ◽  
Author(s):  
S. N. Davies ◽  
G. E. Goldsmith ◽  
R. F. Hellon ◽  
D. Mitchell
Keyword(s):  
Sensory Processing ◽  
Receptive Fields ◽  
Second Order ◽  
Dynamic Responses ◽  
Trigeminal Nucleus ◽  
Afferent Pathway ◽  
Afferent Fibers ◽  
Level Of Activity ◽  
Caudal Trigeminal Nucleus ◽  
High Level

Extracellular recordings were made from cold-receptive afferent fibers in the trigeminal ganglion of rats anesthetized with halothane. By applying a standardized series of steady or changing temperatures to the receptive fields, we recorded the static and dynamic responses of the afferents. Comparable recordings were made from neurons in the marginal layer of the caudal trigeminal nucleus onto which the cold fibers synapse. The static and dynamic responses of the afferent fibers were reproduced faithfully by the second-order neurons, but at a much higher level of activity. Ganglionectomy silenced the second-order cells. Their continuous high level of activity appears to depend on the tonic input from the afferent fibers and not on any intrinsic circuits in the medulla.

Postsynaptic Dorsal Column and Cuneate Correlations in the Raccoon: A Re-evaluation by Parallel-Cascade Analysis

2002 ◽  
Vol 88 (6) ◽  
pp. 3372-3376
Author(s):  
Andrew S. French ◽  
Susan H. Dick ◽  
Douglas D. Rasmusson
Keyword(s):  
Cross Correlation ◽  
Volterra Series ◽  
Receptive Fields ◽  
Dorsal Column ◽  
Second Order ◽  
Input Signals ◽  
Cascade Analysis ◽  
Postsynaptic Dorsal Column ◽  
Positive Correlations ◽  
Cascade Method

In a previous study, we reported evidence for correlations between the firing of postsynaptic dorsal column (PSDC) neurons and cuneate neurons with overlapping receptive fields on the glabrous skin of the raccoon forepaw. The evidence was based on cross-correlation and frequency response analyses of spontaneously firing neurons. However, cross-correlation without white noise Gaussian analog inputs or Poisson distributed pulse train inputs is difficult to interpret because of the inherent convolution with the autocorrelation of the unknown input signals. While the data suggested positive correlations in the spinocuneate direction for most neuron pairs, we could not estimate the temporal characteristics of these putative connections. We have now re-analyzed these data using a parallel-cascade method to estimate the first- and second-order kernels of a Volterra series approximation to the spinocuneate system. This unbiased analysis suggests that a positive correlation occurs after about 5 ms, probably followed by a negative correlation at about 12 ms. Second-order kernels also had repeatable structure, indicating dual pathways with time separations of at least 10 ms.

A Comparison of Møller-Plesset and Coupled Cluster Linear Response Theory Methods for the Calculation of Dipole Oscillator Strength Sum Rules and C6 Dispersion Coefficients

2008 ◽  
Vol 73 (11) ◽  
pp. 1415-1436 ◽  
Author(s):  
Ivana Paidarová ◽  
Stephan P. A. Sauer
Keyword(s):  
Oscillator Strength ◽  
Linear Response ◽  
Sum Rules ◽  
Linear Response Theory ◽  
Second Order ◽  
Coupled Cluster ◽  
Response Theory ◽  
Polarization Propagator ◽  
Dipole Oscillator ◽  
Moller Plesset

Four correlated linear response theory methods - the second order polarization propagator approximation (SOPPA), the second order polarization propagator approximation with coupled cluster singles and doubles amplitudes, SOPPA(CCSD), the CC2 and coupled cluster singles doubles (CCSD) linear response theory - were used to determine the dipole oscillator strength sum rules of the hydrogen halides HX (with X = F, Cl, Br and I) and the C6 dispersion coefficient for all pairs of interacting HX molecules via numerical integration of the Casimir-Polder formula. The dependence of the polarizabilities, their frequency dependence and the C6 coefficients on the level of correlation and the dependence of the C6 coefficients on the two intramolecular bond lengths were studied.

Cone Inputs to Simple and Complex Cells in V1 of Awake Macaque

2007 ◽  
Vol 97 (4) ◽  
pp. 3070-3081 ◽  
Author(s):  
Gregory D. Horwitz ◽  
E. J. Chichilnisky ◽  
Thomas D. Albright
Keyword(s):  
Linear Models ◽  
Noise Analysis ◽  
Receptive Fields ◽  
Light Responses ◽  
Simple Cells ◽  
Complex Cells ◽  
V1 Neurons ◽  
Spike Triggered Averaging ◽  
Simple And Complex Cells ◽  
Simple And Complex Cell

Rules by which V1 neurons combine signals originating in the cone photoreceptors are poorly understood. We measured cone inputs to V1 neurons in awake, fixating monkeys with white-noise analysis techniques that reveal properties of light responses not revealed by purely linear models used in previous studies. Simple cells were studied by spike-triggered averaging that is robust to static nonlinearities in spike generation. This analysis revealed, among heterogeneously tuned neurons, two relatively discrete categories: one with opponent L- and M-cone weights and another with nonopponent cone weights. Complex cells were studied by spike-triggered covariance, which identifies features in the stimulus sequence that trigger spikes in neurons with receptive fields containing multiple linear subunits that combine nonlinearly. All complex cells responded to nonopponent stimulus modulations. Although some complex cells responded to cone-opponent stimulus modulations too, none exhibited the pure opponent sensitivity observed in many simple cells. These results extend the findings on distinctions between simple and complex cell chromatic tuning observed in previous studies in anesthetized monkeys.

scholarly journals Nonlinear temporal receptive fields of neurons in the dorsal cochlear nucleus

2013 ◽  
Vol 110 (10) ◽  
pp. 2414-2425 ◽  
Author(s):  
Sharba Bandyopadhyay ◽  
Eric D. Young
Keyword(s):  
Cochlear Nucleus ◽  
Receptive Fields ◽  
Sound Level ◽  
Second Order ◽  
Dorsal Cochlear Nucleus ◽  
Spectral Processing ◽  
Low Contrast ◽  
Response Properties ◽  
First Order ◽  
Order Components

Studies of the dorsal cochlear nucleus (DCN) have focused on spectral processing because of the complex spectral receptive fields of the DCN. However, temporal fluctuations in natural signals convey important information, including information about moving sound sources or movements of the external ear in animals like cats. Here, we investigate the temporal filtering properties of DCN principal neurons through the use of temporal weighting functions that allow flexible analysis of nonlinearities and time variation in temporal response properties. First-order temporal receptive fields derived from the neurons are sufficient to characterize their response properties to low-contrast (3-dB standard deviation) stimuli. Larger contrasts require the second-order terms. Allowing temporal variation of the parameters of the first-order model or adding a component representing refractoriness improves predictions by the model by relatively small amounts. The importance of second-order components of the model is shown through simulations of nonlinear envelope synchronization behavior across sound level. The temporal model can be combined with a spectral model to predict tuning to the speed and direction of moving sounds.

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