Modulation of neuronal dynamic range using two different adaptation mechanisms

Adaptation, a change in response to a sustained stimulus, is a widespread property of sensory systems, occurring at many stages, from the most peripheral energy-gathering structures to neural networks. Adaptation is also implemented at many levels of biological organization, from the molecule to the organ. Despite adaptation's diversity, it is fruitful to extract some unifying principles by considering well-characterized components of the insect visual system. A major function of adaptation is to increase the amount of sensory information an organism uses. The amount of information available to an organism is ultimately defined by its environment and its size. The amount of information collected depends upon the ways in which an organism samples and transduces signals. The amount of information that is used is further limited by internal losses during transmission and processing. Adaptation can increase information capture and reduce internal losses by minimizing the effects of physical and biophysical constraints. Optical adaptation mechanisms in compound eyes illustrate a common trade-off between energy (quantum catch) and acuity (sensitivity to changes in the distribution of energy). This trade-off can be carefully regulated to maximize the information gathered (i.e. the number of pictures an eye can reconstruct). Similar trade-offs can be performed neurally by area summation mechanisms. Light adaptation in photoreceptors introduces the roles played by cellular constraints in limiting the available information. Adaptation mechanisms prevent saturation and, by trading gain for temporal acuity, increase the rate of information uptake. By minimizing the constraint of nonlinear summation (imposed by membrane conductance mechanisms) a cell's sensitivity follows the Weber-Fechner law. Thus, a computationally advantageous transformation is generated in response to a cellular constraint. The synaptic transfer of signals from photoreceptors to second-order neurones emphasizes that the cellular constraints of nonlinearity, noise and dynamic range limit the transmission of information from cell to cell. Synaptic amplification is increased to reduce the effects of noise but this resurrects the constraint of dynamic range. Adaptation mechanisms, both confined to single synapses and distributed in networks, remove spatially and temporally redundant signal components to help accommodate more information within a single cell. The net effect is a computationally advantageous removal of the background signal. Again, the cellular constraints on information transfer have dictated a computationally advantageous operation.

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Active Dendrites Enhance Neuronal Dynamic Range

PLoS Computational Biology ◽

10.1371/journal.pcbi.1000402 ◽

2009 ◽

Vol 5 (6) ◽

pp. e1000402 ◽

Cited By ~ 39

Author(s):

Leonardo L. Gollo ◽

Osame Kinouchi ◽

Mauro Copelli

Keyword(s):

Dynamic Range ◽

Active Dendrites ◽

Neuronal Dynamic

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Review for "Light adaptation mechanisms in the eye of the fiddler crab Afruca tangeri"

10.1002/cne.24973/v1/review2 ◽

2020 ◽

Keyword(s):

Light Adaptation ◽

Fiddler Crab ◽

Adaptation Mechanisms

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Decision letter for "Light adaptation mechanisms in the eye of the fiddler crab Afruca tangeri"

10.1002/cne.24973/v2/decision1 ◽

2020 ◽

Keyword(s):

Light Adaptation ◽

Fiddler Crab ◽

Adaptation Mechanisms

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Slow-Scan CCD Observation of Backscattering Patterns in SEM

Proceedings, annual meeting, Electron Microscopy Society of America ◽

10.1017/s0424820100131176 ◽

1992 ◽

Vol 50 (2) ◽

pp. 1308-1309

Author(s):

F. Ouyang ◽

D. A. Ray ◽

O. L. Krivanek

Keyword(s):

Electron Beam ◽

Electron Microscope ◽

Scanning Electron Microscope ◽

Dynamic Range ◽

High Sensitivity ◽

Lens System ◽

Wide Dynamic Range ◽

Peltier Cooler ◽

Diffraction Patterns ◽

Scanning Electron

Electron backscattering Kikuchi diffraction patterns (BKDP) reveal useful information about the structure and orientation of crystals under study. With the well focused electron beam in a scanning electron microscope (SEM), one can use BKDP as a microanalysis tool. BKDPs have been recorded in SEMs using a phosphor screen coupled to an intensified TV camera through a lens system, and by photographic negatives. With the development of fiber-optically coupled slow scan CCD (SSC) cameras for electron beam imaging, one can take advantage of their high sensitivity and wide dynamic range for observing BKDP in SEM.We have used the Gatan 690 SSC camera to observe backscattering patterns in a JEOL JSM-840A SEM. The CCD sensor has an active area of 13.25 mm × 8.83 mm and 576 × 384 pixels. The camera head, which consists of a single crystal YAG scintillator fiber optically coupled to the CCD chip, is located inside the SEM specimen chamber. The whole camera head is cooled to about -30°C by a Peltier cooler, which permits long integration times (up to 100 seconds).

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Quantitative energy-filtered electron diffraction

Proceedings, annual meeting, Electron Microscopy Society of America ◽

10.1017/s0424820100172693 ◽

1994 ◽

Vol 52 ◽

pp. 992-993

Author(s):

R. Vincent

Keyword(s):

Electron Diffraction ◽

Inelastic Scattering ◽

Dynamic Range ◽

Electron Optics ◽

Surface Layers ◽

High Brightness ◽

Inclined Surfaces ◽

Perfect Symmetry ◽

Amorphous Surface ◽

The Ideal

Microanalysis and diffraction on a sub-nanometre scale have become practical in modern TEMs due to the high brightness of field emission sources combined with the short mean free paths associated with both elastic and inelastic scattering of incident electrons by the specimen. However, development of electron diffraction as a quantitative discipline has been limited by the absence of any generalised theory for dynamical inelastic scattering. These problems have been simplified by recent innovations, principally the introduction of spectrometers such as the Gatan imaging filter (GIF) and the Zeiss omega filter, which remove the inelastic electrons, combined with annual improvements in the speed of computer workstations and the availability of solid-state detectors with high resolution, sensitivity and dynamic range.Comparison of experimental data with dynamical calculations imposes stringent requirements on the specimen and the electron optics, even when the inelastic component has been removed. For example, no experimental CBED pattern ever has perfect symmetry, departures from the ideal being attributable to residual strain, thickness averaging, inclined surfaces, incomplete cells and amorphous surface layers.

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Direct measurement of electron-diffraction-pattern intensities using an energy loss spectrometer

Proceedings, annual meeting, Electron Microscopy Society of America ◽

10.1017/s0424820100155311 ◽

1989 ◽

Vol 47 ◽

pp. 668-669

Author(s):

A. G. Jackson ◽

M. Rowe

Keyword(s):

Thermal Effects ◽

Dynamic Range ◽

Scattering Amplitude ◽

Dynamical Theory ◽

Site Symmetry ◽

Proof Of Concept ◽

Parallel Acquisition ◽

Kinematic Approximation ◽

Speed Up ◽

Structure Calculations

Diffraction intensities from intermetallic compounds are, in the kinematic approximation, proportional to the scattering amplitude from the element doing the scattering. More detailed calculations have shown that site symmetry and occupation by various atom species also affects the intensity in a diffracted beam. [1] Hence, by measuring the intensities of beams, or their ratios, the occupancy can be estimated. Measurement of the intensity values also allows structure calculations to be made to determine the spatial distribution of the potentials doing the scattering. Thermal effects are also present as a background contribution. Inelastic effects such as loss or absorption/excitation complicate the intensity behavior, and dynamical theory is required to estimate the intensity value.The dynamic range of currents in diffracted beams can be 104or 105:1. Hence, detection of such information requires a means for collecting the intensity over a signal-to-noise range beyond that obtainable with a single film plate, which has a S/N of about 103:1. Although such a collection system is not available currently, a simple system consisting of instrumentation on an existing STEM can be used as a proof of concept which has a S/N of about 255:1, limited by the 8 bit pixel attributes used in the electronics. Use of 24 bit pixel attributes would easily allowthe desired noise range to be attained in the processing instrumentation. The S/N of the scintillator used by the photoelectron sensor is about 106 to 1, well beyond the S/N goal. The trade-off that must be made is the time for acquiring the signal, since the pattern can be obtained in seconds using film plates, compared to 10 to 20 minutes for a pattern to be acquired using the digital scan. Parallel acquisition would, of course, speed up this process immensely.

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