The time course of sensory adaptation in the cockroach tactile spine

RNA interference supports a role for Nanchung-Inactive in mechanotransduction by the cockroach, Periplaneta americana, tactile spine

Proteins encoded by nanchung, inactive, nompC and piezo genes have been shown to play crucial roles in the initial detection of mechanical force by various insect auditory neurons, nociceptors and touch receptors. Most of this previous research has been performed on the larval and adult fruit fly, Drosophila melanogaster. We identified and assembled all four homologous genes in transcriptomes from the cockroach, Periplaneta americana. Injection of long double-stranded RNA (dsRNA) into the adult cockroach abdomen successfully reduced the expression of each gene, as measured by quantitative PCR (RT-qPCR). A simple electrophysiological assay was used to record action potential firing in afferent nerves of cockroach femoral tactile spines in response to a standardized mechanical step displacement. Responses of nanchung knockdown animals were significantly reduced compared to matched sham-injected animals at 14 and 21 days after injection, and inactive knockdowns similarly at 21 days. In contrast, responses of nompC and piezo knockdowns were unchanged. Our results support a model in which Nanchung and Inactive proteins combine to form a part of the mechanotransduction mechanism in the cockroach tactile spine.

The systems analysis approach to mechanosensory coding

An important problem in neuroscience is to obtain quantitative knowledge of how information is represented, or encoded, in the signals that nerve cells process and transmit. Sensory receptors have provided important models for the study of neural coding because their inputs can often be relatively easily controlled and measured, while the resultant activity is recorded. A variety of engineering concepts have been successfully applied to physiological sciences, particularly those related to control of dynamic systems. Linear systems analysis was one of the earliest methods used to probe sensory coding, and measurements such as step responses and frequency responses have become standard tools for describing sensory functions. Modern systems analysis has evolved to provide accurate and efficient linear identification of encoding in sensory receptors that use either graded potentials or action potentials. It has also led to nonlinear systems analysis, the creation of parametric nonlinear models, and measures of information coding by sensory neurons. These methods promise to provide important new knowledge about sensory systems in the future, especially when complemented with parallel biophysical and molecular studies of sensory neurons. Mechanoreceptors provided some of the earliest preparations for the investigation of neural coding, and both the linear and nonlinear properties of wide variety of vertebrate and invertebrate mechanoreceptors continue to be explored.

The power law of sensory adaptation: simulation by a model of excitability in spider mechanoreceptor neurons

The power law of sensory adaptation was introduced more than 50 years ago. It is characterized by action potential adaptation that follows fractional powers of time or frequency, rather than exponential decays and corresponding frequency responses. Power law adaptation describes the responses of a range of vertebrate and invertebrate sensory receptors to deterministic stimuli, such as steps or sinusoids, and to random (white noise) stimulation. Hypotheses about the physical basis of power law adaptation have existed since its discovery. Its cause remains enigmatic, but the site of power law adaptation has been located in the conversion of receptor potentials into action potentials in some preparations. Here, we used pseudorandom noise stimulation and direct spectral estimation to show that simulations containing only two voltage activated currents can reproduce the power law adaptation in two types of spider mechanoreceptors. Identical simulations were previously used to explain the different responses of these two types of sensory neurons to step inputs. We conclude that power law adaptation results during action potential encoding by nonlinear combination of a small number of activation and inactivation processes with different exponential time constants.

Spike-frequency adaptation generates intensity invariance in a primary auditory interneuron

Adaptation of the spike-frequency response to constant stimulation, as observed on various timescales in many neurons, reflects high-pass filter properties of a neuron's transfer function. Adaptation in general, however, is not sufficient to make a neuron's response independent of the mean intensity of a sensory stimulus, since low frequency components of the stimulus are still transmitted, although with reduced gain. We here show, based on an analytically tractable model, that the response of a neuron is intensity invariant, if the fully adapted steady-state spike-frequency response to constant stimuli is independent of stimulus intensity. Electrophysiological recordings from the AN1, a primary auditory interneuron of crickets, show that for intensities above 60 dB SPL (sound pressure level) the AN1 adapted with a time-constant of approximately 40 ms to a steady-state firing rate of approximately 100 Hz. Using identical random amplitude-modulation stimuli we verified that the AN1's spike-frequency response is indeed invariant to the stimulus' mean intensity above 60 dB SPL. The transfer function of the AN1 is a band pass, resulting from a high-pass filter (cutoff frequency at 4 Hz) due to adaptation and a low-pass filter (100 Hz) determined by the steady-state spike frequency. Thus, fast spike-frequency adaptation can generate intensity invariance already at the first level of neural processing.

Slow adaptation in spider mechanoreceptor neurons

Slow adaptation of action potential firing is a common but poorly understood property of sensory neurons. We quantified slow adaptation in a cuticular mechanoreceptor organ of the spider, Cupiennius salei, by stimulating with continuous pseudorandom mechanical displacements while recording action potentials intracellularly from the cell bodies. Firing rate declined over a period of several minutes before reaching a steady level at about half the initial rate. This slow adaptation was fitted by an exponential decay with mean time constant of 18.5 s. Recovery from slow adaptation was also fitted by an exponential process, but with a longer time constant of 167 s. The receptor potential produced by the same stimulation protocol did not change its amplitude or dynamics, showing that slow adaptation occurs during action potential encoding from the receptor potential. Experiments with chemical blockers of calcium entry or the known potassium currents failed to reduce the slow adaptation. The Na+/K+ pump blocker Ouabain decreased the time constant of slow adaptation, suggesting that ion accumulation is involved. In some experiments, a second class of small action potentials were observed, which were tentatively attributed to failed conduction from the sensory dendrite through the soma to the axon.