Spatial summation in the human fovea measured with adaptive optics

AbstractPsychophysical inferences about the neural mechanisms supporting spatial vision can be undermined by uncertainties introduced by optical aberrations and fixational eye movements, particularly in fovea where the neuronal grain of the visual system is fine. We examined the effect of these pre-neural factors on photopic spatial summation in the human fovea using a custom adaptive optics scanning light ophthalmoscope that provided control over optical aberrations and retinal stimulus motion. Consistent with previous results, Ricco’s area of complete summation encompassed multiple photoreceptors when measured with ordinary amounts of ocular aberrations and retinal stimulus motion. When both factors were minimized experimentally, summation areas were essentially unchanged, suggesting that foveal spatial summation is limited by post-receptoral neural pooling. We compared our behavioral data to predictions generated with a physiologically-inspired front-end model of the visual system, and were able to capture the shape of the summation curves obtained with and without pre-retinal factors using a single post-receptoral summing filter of fixed spatial extent. Given our data and modeling, neurons in the magnocellular visual pathway, such as parasol ganglion cells, provide a candidate neural correlate of Ricco’s area in the central fovea.

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Spatial summation of individual cones in human color vision

10.1101/521492 ◽

2019 ◽

Author(s):

Brian P. Schmidt ◽

Alexandra E. Boehm ◽

William S. Tuten ◽

Austin Roorda

Keyword(s):

Adaptive Optics ◽

Spatial Summation ◽

Relative Activity ◽

Excitatory Input ◽

Color Information ◽

Parvocellular Pathway ◽

Spectral Class ◽

Target Individual ◽

Single Cone ◽

Human Color Vision

AbstractThe human retina contains three classes of cone photoreceptors each sensitive to different portions of the visual spectrum: long (L), medium (M) and short (S) wavelengths. Color information is computed by downstream neurons that compare relative activity across the three cone types. How cone signals are combined at a cellular scale has been more difficult to resolve. This is especially true near the fovea, where spectrally-opponent neurons in the parvocellular pathway draw excitatory input from a single cone and thus even the smallest stimulus will engage multiple color-signaling neurons. We used an adaptive optics microstimulator to target individual and pairs of cones with light. Consistent with prior work, we found that color percepts elicited from individual cones were predicted by their spectral sensitivity, although there was considerable variability even between cones within the same spectral class. The appearance of spots targeted at two cones were predicted by an average of their individual activations. However, two cones of the same subclass elicited percepts that were systematically more saturated than predicted by an average. Together, these observations suggest both spectral opponency and prior experience influence the appearance of small spots.

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Adaptive optics (astronomy)

AccessScience ◽

10.1036/1097-8542.yb990105 ◽

2015 ◽

Keyword(s):

Adaptive Optics

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Adaptive optics with adaptive filtering and control

Proceedings of the 2004 American Control Conference ◽

10.23919/acc.2004.1384398 ◽

2004 ◽

Author(s):

Yu-Tai Liu ◽

S. Gibson

Keyword(s):

Adaptive Optics ◽

Adaptive Filtering ◽

And Control

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Accounting for mirror dynamics in optimal Adaptive Optics control

2009 European Control Conference (ECC) ◽

10.23919/ecc.2009.7074944 ◽

2009 ◽

Cited By ~ 1

Author(s):

Carlos Correia ◽

Henri-Francois Raynaud ◽

Caroline Kulcsar ◽

Jean-Marc Conan

Keyword(s):

Adaptive Optics

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The Condition for Absolute Stability of an Electroelastic Actuator Control System for Nanomechatronics

Elektrichestvo ◽

10.24160/0013-5380-2020-10-52-58 ◽

2020 ◽

Vol 10 (10) ◽

pp. 52-58

Author(s):

Sergey M. AFONIN ◽

Keyword(s):

Control System ◽

Adaptive Optics ◽

Absolute Stability ◽

Deformation Characteristic ◽

Straight Line Segment ◽

Control Mechanisms ◽

Relative Width ◽

Random Inputs ◽

Deformation Control ◽

Actuator Control

An electroelastic actuator for nanomechatronics is used in nanotechnology, adaptive optics, microsurgery, microelectronics, and biomedicine to actuate or control mechanisms, systems based on the electroelastic effect, and to convert electrical signals into mechanical displacements and forces. In nanomechatronic systems, a piezoactuator is used in scanning microscopy, laser systems, in astronomy for precision alignment, for compensation of temperature, gravitational deformations and atmospheric turbulence, focusing, and stabilizing the image. In this study, a condition for absolute stability of an electroelastic actuator control system for nanomechatronics under deterministic and random inputs is obtained. A number of equilibrium positions in an electroelastic actuator mechatronic control system are found, the totality of which is represented by a straight line segment. The electroelastic actuator’s deformation control system dead band relative width is determined for the actuator’s symmetric and asymmetric hysteresis characteristics. Under deterministic inputs and with fulfilling the condition for the derivative of the nonlinear hysteresis actuator deformation characteristic, the set of equilibrium positions of the electroelastic actuator control system for nanomechatronics is absolutely stable. Under random inputs, the system absolute stability with respect to the mathematical expectations of the electroelastic actuator mechatronic control system equilibrium positions has been determined subject to fulfilling the condition on the derivative of the actuator hysteresis characteristic.

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