Nociceptors--noxious stimulus detectors

In order to deal effectively with danger, it is imperative to know about it. This is what nociceptors do--these primary sensory neurons are specialized to detect intense stimuli and represent, therefore, the first line of defense against any potentially threatening or damaging environmental inputs. By sensing noxious stimuli and contributing to the necessary reactions to avoid them--rapid withdrawal and the experience of an intensely unpleasant or painful sensation, nociceptors are essential for the maintenance of the body's integrity. Although nociceptive pain is clearly an adaptive alarm system, persistent pain is maladaptive, essentially an ongoing false alarm. Here, we highlight the genesis of nociceptors during development and the intrinsic properties of nociceptors that enable them to transduce, conduct, and transmit nociceptive information and also discuss how their phenotypic plasticity contributes to clinical pain.     

Flux detectors versus concentration detectors: two types of chemoreceptors

Dose-response curves relating the external stimulus concentration to receptor occupancy differ in two types of chemoreceptor organs. In 'concentration detectors' the receptor molecules at the receptor cell membrane are directly exposed to the external stimulus concentration; these organs exhibit the well-known hyperbolic dose-response relationship reflecting the association-dissociation of stimulus and receptor molecules. In contrast, 'flux detectors' accumulate the stimulus molecules in a perireceptor compartment. In flux detectors, deactivation of stimulus molecules may be in balance with arrival, as a prerequisite for producing a constant effective stimulus concentration at constant adsorptive flux of stimulus molecules. In a simple model of a flux detector in which receptor molecules themselves catalyze the deactivation, the dose-response relationship is linear. It reflects the rate of stimulus deactivation. If the deactivation is catalyzed by a separate enzyme, the dose-response relationship can be close to hyperbolic, or linear. In all cases, the receptor molecules are maximally occupied if the adsorptive flux equals or exceeds the maximum rate of stimulus deactivation. The time course of the receptor potential recorded from moths' pheromone receptors depends on the odor compound, which suggests that a peripheral process, possibly the stimulus deactivation, is the slowest, rate-limiting process of the transduction cascade. Further evidence comes from experiments with stimuli oversaturating the mechanism responsible for the decline of the receptor potential.      

Electronic detectors for electron microscopy

Due to the increasing popularity of electron cryo-microscopy (cryoEM) in the structural analysis of large biological molecules and macro-molecular complexes and the need for simple, rapid and efficient readout, there is a persuasive need for improved detectors. Commercial detectors, based on phosphor/fibre optics-coupled CCDs, provide adequate performance for many applications, including electron diffraction. However, due to intrinsic light scattering within the phosphor, spatial resolution is limited. Careful measurements suggest that CCDs have superior performance at lower resolution while all agree that film is still superior at higher resolution. Consequently, new detectors are needed based on more direct detection, thus avoiding the intermediate light conversion step required for CCDs. Two types of direct detectors are discussed in this review. First, there are detectors based on hybrid technology employing a separate pixellated sensor and readout electronics connected with bump bonds-hybrid pixel detectors (HPDs). Second, there are detectors, which are monolithic in that sensor and readout are all in one plane (monolithic active pixel sensor, MAPS). Our discussion is centred on the main parameters of interest to cryoEM users, viz. detective quantum efficiency (DQE), resolution or modulation transfer function (MTF), robustness against radiation damage, speed of readout, signal-to-noise ratio (SNR) and the number of independent pixels available for a given detector.     

Electronic detectors for electron microscopy

Electron microscopy (EM) is an important tool for high-resolution structure determination in applications ranging from condensed matter to biology. Electronic detectors are now used in most applications in EM as they offer convenience and immediate feedback that is not possible with film or image plates. The earliest forms of electronic detector used routinely in transmission electron microscopy (TEM) were charge coupled devices (CCDs) and for many applications these remain perfectly adequate. There are however applications, such as the study of radiation-sensitive biological samples, where film is still used and improved detectors would be of great value. The emphasis in this review is therefore on detectors for use in such applications. Two of the most promising candidates for improved detection are: monolithic active pixel sensors (MAPS) and hybrid pixel detectors (of which Medipix2 was chosen for this study). From the studies described in this review, a back-thinned MAPS detector appears well suited to replace film in for the study of radiation-sensitive samples at 300 keV, while Medipix2 is suited to use at lower energies and especially in situations with very low count rates. The performance of a detector depends on the energy of electrons to be recorded, which in turn is dependent on the application it is being used for; results are described for a wide range of electron energies ranging from 40 to 300 keV. The basic properties of detectors are discussed in terms of their modulation transfer function (MTF) and detective quantum efficiency (DQE) as a function of spatial frequency.     

Neurons as ideal change-point detectors

Every computational unit in the brain monitors incoming signals, instant by instant, for meaningful changes in the face of stochastic fluctuation. Recent studies have suggested that even a single neuron can detect changes in noisy signals. In this paper, we demonstrate that a single leaky integrate-and-fire neuron can achieve change-point detection close to that of theoretical optimal, for uniform-rate process, functions even better than a Bayes-optimal algorithm when the underlying rate deviates from a presumed uniform rate process. Given a reasonable number of synaptic connections (order 10⁴) and the rate of the input spike train, the values of the membrane time constant and the threshold found for optimizing change-point detection are close to those seen in biological neurons. These findings imply that biological neurons could act as sophisticated change-point detectors.     

Functional proteomics using microchannel plate detectors

We describe the development of a novel detection system used for the functional imaging of proteins separated on electrophoretic gels. A microchannel plate detector is used here for real-time imaging of low levels of tritiated protein separated by two-dimensional (2-D) electrophoresis. The system employs radioisotope-free, low noise microchannel plates originally developed for photon counting in X-ray astronomy. Using the detector configuration described here, proteins were resolved on mini gels by either one or two-dimensional electrophoresis, transferred onto polyvinylidene difluoride membranes and directly imaged. Tritiated diisopropylfluorophosphate (DFP) was used as a selective label for the serine hydrolase class of enzymes and their distribution in the central nervous system was examined. This survey revealed approximately 24 protein spots by 2-D electrophoresis. We also investigated the relative sensitivity of these proteins towards DFP and found the peptidase, acylpeptide hydrolase to be the most sensitive brain protein towards this reagent. Using a number of different tritiated standards, it was found that the system can image as little as 0.1 Bq/mm(2) of tritium corresponding to 320 attomol of DFP labelled protein/mm(2). Moreover, the system has a wide dynamic range (>10(6)) allowing samples of high and low activity to be quantified on the same gel.     

Light sharing in multi-flat-panel-PMT PEM detectors

Large are a detectors, such as those used in positron emission mammography (PEM) and scintimammography, utilize arrays of discrete semtillator elements mounted on arrays of position sensitive photomultiplier tubes (PSPMT). Scintillator elements can be packed very densely (minimizing area between elements), allowing good detection sensitivity and spatial resolution. And, while new flat panel PSPMTS have minimal inactive edges, when they are placed in arrays significant dead spaces where scintillation light is undetectable are created. To address this problem, a light guide is often placed between the detector and PSPMT array to spread scintillation light so that these gaps can be bridged. In this investigation we studied the effect of light guides of various thickness on system performance. A 10×10 element array of LYSO detector elements was coupled to the center of a 2×2 array of PSPMTs through varying thicknesses (1 to 4 mm) of UV glass. The spot size of the imaged elements and distortions in the regular square pattern of the imaged scintillator arrays were evaluated. Energy resolution was measured by placing single elements of LYSO at several locations of the PSPMT array. Spatial distortions in the images of the array were reduced by using thicker light guides (3–4 mm). Use of thicker light guides, however, resulted in reduced pixel resolution and slight degradation of energy resolution. Therefore, some loss of pixel and energy resolution will accompany the use of thick light guides (minimum of 3 mm) required for optimum identification of detector elements.     

Development of feature detectors by self-organization

We present a two-layered network of linear neurons that organizes itself as to extract the complete information contained in a set of presented patterns. The weights between layers obey a Hebbian rule. We propose a local anti-Hebbian rule for lateral, hierarchically organized weights within the output layer. This rule forces the activities of the output units to become uncorrelated and the lateral weights to vanish. The weights between layers converge to the eigenvectors of the covariance matrix of input patterns, i.e., the network performs a principal component analysis, yielding all principal components. As a consequence of the proposed learning scheme, the output units become detectors of orthogonal features, similar to ones found in the brain of mammals.     

Polarization vision in crayfish motion detectors

Motion detector interneurons were examined to determine their responsiveness to the motion of polarized light images (i.e. images segmented by spatial variations in e-vector angle). Computer generated images were displayed as intensity contrasts or polarization contrasts on a modified LCD projection panel. The stimuli included the motion of a single stripe (45 degrees -55 degrees /s) and the global motion of a square wave grating (3.3 degrees /s). Neurons were impaled in the medulla interna. Of the neurons which exhibited a directional response to the motion of intensity contrast stimuli, about 2/3 were also directional in the response to polarized light images. Transient (nondirectional) stimuli included looming and jittery motions. The responses to the transient motions of the polarized light images were roughly comparable to those elicited by intensity contrast. The results imply that behavioral responses to polarized light images (i.e. optokinetic and defense reflexes) may have a basis in the polarization sensitivity and synaptic organization of the medulla interna.     

On the directional sensitivity of motion detectors

The output of a motion detector depends on the direction of pattern motion, relative to the axis defined by its two input elements. Usually a cosine shaped directional sensitivity characteristics is assumed: The response is strongest for pattern motion along the detector axis, reversing its sign for motion in opposite direction; for motion perpendicular to the detector axis it is expected to be zero, with intermediate values for oblique motion directions. However, geometric considerations show that this expectation is by no means trivial. When a periodic pattern moves along a direction a relative to the detector axis, the spatiotemporal intensity distribution along the detector axis can be described by its apparent spatial wavelength and its apparent velocity, which both vary with 1/cos. In consequence, a motion detector depending exclusively on the apparent velocity of the stimulus would respond strongest to gratings moving perpendicular to the detector axis, whereas motion along the detector axis would yield the smallest response in such a detector. The response of a motion detector of the correlation type, on the other hand, is determined by the ratio between velocity and wavelength, the temporal frequency, which is not influenced by the direction of pattern motion, and by the ratio between sampling base and the wavelength. The latter feature leads to a cosine-shaped directional characteristics for large pattern wavelengths. However, for smaller wavelengths specific deviations from a simple harmonic are expected. These expectations were confirmed by the simulation of an elementary motion detector model and extended for a slightly more elaborated model. Representing a biological motion detecting unit of the correlation type, the directional characteristics of the H1 interneuron in the fly's brain was investigated electrophysiologically, and compared to the simulations.     

Computation of optical motion by movement detectors

The first part of this paper deals with a system-theoretical approach for the decomposition of multi-input systems into the sum of simpler systems. This approach is applied here to analyse the algorithm which represents the computations underlying the extraction of motion information from the optical environment by biological movement detectors. The second part concentrates on a specific model for motion computation known to be realized by the visual system of insects and of man. These detectors provide the visual system with information on both the velocity and structural properties of a moving pattern. In the third part of this article the properties of two-dimensional arrays of movement detectors are analyzed and their relations to meaningful physiological responses are discussed.     

Image plate detectors for macromolecular neutron diffractometry

Neutron diffraction studies of macromolecules require large position sensitive detectors. It is proposed that such a device can be based on image plate technology, which relies on re-usable photostimuable phosphors, combined with a neutron to gamma-ray converter. Design parameters such as the best wavelength for the neutron radiation and the optimum sample to detector distance are discussed, and a design for a cylindrical detector is outlined. Presently a prototype of such a detector is being built, and the very first test-recording of an X-ray diffraction pattern from a protein crystal is presented.     

High-energy neutron spectroscopy with thick silicon detectors

The high-energy neutron component of the space radiation environment in thick structures such as the International Space Station contributes to the total radiation dose received by an astronaut. Detector design constraints such as size and mass have limited the energy range of neutron spectrum measurements in orbit to about 12 MeV in Space Shuttle studies. We present a new method for high-energy neutron spectroscopy using small silicon detectors that can extend these measurements to more than 500 MeV. The methodology is based on measurement of the detector response function for high-energy neutrons and inversion of this response function with measured deposition data to deduce neutron energy spectra. We also present the results of an initial shielding study performed with the thick silicon detector system for high-energy neutrons incident on polyethylene.