Adaptation and selective information transmission in the cricket auditory neuron AN2

Sensory systems adapt their neural code to changes in the sensory environment, often on multiple time scales. Here, we report a new form of adaptation in a first-order auditory interneuron (AN2) of crickets. We characterize the response of the AN2 neuron to amplitude-modulated sound stimuli and find that adaptation shifts the stimulus-response curves toward higher stimulus intensities, with a time constant of 1.5 s for adaptation and recovery. The spike responses were thus reduced for low-intensity sounds. We then address the question whether adaptation leads to an improvement of the signal's representation and compare the experimental results with the predictions of two competing hypotheses: infomax, which predicts that information conveyed about the entire signal range should be maximized, and selective coding, which predicts that "foreground" signals should be enhanced while "background" signals should be selectively suppressed. We test how adaptation changes the input-response curve when presenting signals with two or three peaks in their amplitude distributions, for which selective coding and infomax predict conflicting changes. By means of Bayesian data analysis, we quantify the shifts of the measured response curves and also find a slight reduction of their slopes. These decreases in slopes are smaller, and the absolute response thresholds are higher than those predicted by infomax. Most remarkably, and in contrast to the infomax principle, adaptation actually reduces the amount of encoded information when considering the whole range of input signals. The response curve changes are also not consistent with the selective coding hypothesis, because the amount of information conveyed about the loudest part of the signal does not increase as predicted but remains nearly constant. Less information is transmitted about signals with lower intensity.     

Simple molecular model for sensing and adaptation based on receptor modification with application to bacterial chemotaxis

A series of simple models to explain adaptation in a sensory system based on reversible covalent modification is developed. The models are applied to the reversible methylation of chemoreceptors in bacteria and by analogy to other sensory transduction systems. The receptor modification system exhibits sensing and adaptation, i.e. raising the stimulus to a new level generates a transient response followed by a return to prestimulus behavior. By means of an analytical solution of the kinetic equation that governs the evolution of the receptor system. an exact expression is obtained for the time required for adaptation. The results account for the most conspicuous properties of the bacterial sensory system; namely, the response times in relation to stimulus changes, the proportionality of receptor modification to receptor occupancy, and the additivity of response times. The analysis indicates how these properties depend upon the parameters of the system, e.g. the rates of covalent modification and demodification, the accuracy of the detector, and the molecular nature of the response regulator. The theory developed for analysis of the bacterial system revealed properties that will be applicable to any system processing sensory information.     

Shifts in coding properties and maintenance of information transmission during adaptation in barrel cortex

Neuronal responses to ongoing stimulation in many systems change over time, or “adapt.” Despite the ubiquity of adaptation, its effects on the stimulus information carried by neurons are often unknown. Here we examine how adaptation affects sensory coding in barrel cortex. We used spike-triggered covariance analysis of single-neuron responses to continuous, rapidly varying vibrissa motion stimuli, recorded in anesthetized rats. Changes in stimulus statistics induced spike rate adaptation over hundreds of milliseconds. Vibrissa motion encoding changed with adaptation as follows. In every neuron that showed rate adaptation, the input–output tuning function scaled with the changes in stimulus distribution, allowing the neurons to maintain the quantity of information conveyed about stimulus features. A single neuron that did not show rate adaptation also lacked input–output rescaling and did not maintain information across changes in stimulus statistics. Therefore, in barrel cortex, rate adaptation occurs on a slow timescale relative to the features driving spikes and is associated with gain rescaling matched to the stimulus distribution. Our results suggest that adaptation enhances tactile representations in primary somatosensory cortex, where they could directly influence perceptual decisions.     

Information und Energie in der Physiologie

Research in sensory physiology proves the usefulness of describing distinct functions of sensory systems from the point of view of information processing, neglecting energetic (metabolic) processes, which may occur simultaneously. On the other hand, complex metabolic processes play an important role in sensory reception and sensory communication. Adaptation — in quite a few situations resulting in an actual gain of sensory information — is based upon interacting metabolic processes. It is conceivable that various enzyme systems, such as coenzyme B, involved in the building and destruction of a particular exitatory substance, e. g., acetylcholine and cholinesterase, influence the speed of these different metabolic processes within the sensory cells. It is even possible to separate the damage done to these processes by using an electrophysiological recording of combined action potentials on the auditory nerve and accounting for the time course of adaptation according toRanke's adaptation theory. The human central nervous system selects the 100 bit/sec processed for conscious perception from the 10⁹ bit/sec offered from all sensory receptors in two principal ways: (1) “Specific auditory information” is modulated by “unspecific” information processed through the reticular formation of the brain stem; (2) descending fiber systems alter selectively the information flow on every level of the auditory pathway. The filtered information perceived, in turn triggers a set of inborn and learned behavioral responses, such as speech and motor reaction, altogether representing appromaximately 10⁷ bit/sec. Metabolic processes possibly involved in this optimizing system are largely unknown.     

Coding Efficiency of Fly Motion Processing Is Set by Firing Rate,Not Firing Precision

To comprehend the principles underlying sensory information processing, it is important to understand how the nervous system deals with various sources of perturbation. Here, we analyze how the representation of motion information in the fly''s nervous system changes with temperature and luminance. Although these two environmental variables have a considerable impact on the fly''s nervous system, they do not impede the fly to behave suitably over a wide range of conditions. We recorded responses from a motion-sensitive neuron, the H1-cell, to a time-varying stimulus at many different combinations of temperature and luminance. We found that the mean firing rate, but not firing precision, changes with temperature, while both were affected by mean luminance. Because we also found that information rate and coding efficiency are mainly set by the mean firing rate, our results suggest that, in the face of environmental perturbations, the coding efficiency is improved by an increase in the mean firing rate, rather than by an increased firing precision.     

Variable sizes of Escherichia coli chemoreceptor signaling teams

Like many sensory receptors, bacterial chemotaxis receptors form clusters. In bacteria, large‐scale clusters are subdivided into signaling teams that act as ‘antennas’ allowing detection of ligands with remarkable sensitivity. The range of sensitivity is greatly extended by adaptation of receptors to changes in concentrations through covalent modification. However, surprisingly little is known about the sizes of receptor signaling teams. Here, we combine measurements of the signaling response, obtained from in vivo fluorescence resonance energy transfer, with the statistical method of principal component analysis, to quantify the size of signaling teams within the framework of the previously successful Monod–Wyman–Changeux model. We find that size of signaling teams increases 2‐ to 3‐fold with receptor modification, indicating an additional, previously unrecognized level of adaptation of the chemotaxis network. This variation of signaling‐team size shows that receptor cooperativity is dynamic and likely optimized for sensing noisy ligand concentrations.     

Nonadaptive Fluctuation in an Adaptive Sensory System: Bacterial Chemoreceptor

Background

Sensory systems often exhibit an adaptation or desensitization after a transient response, making the system ready to receive a new signal over a wide range of backgrounds. Because of the strong influence of thermal stochastic fluctuations on the biomolecules responsible for the adaptation, such as many membrane receptors and channels, their response is inherently noisy, and the adaptive property is achieved as a statistical average.

Methodology/Principal Findings

Here, we study a simple kinetic model characterizing the essential aspects of these adaptive molecular systems and show theoretically that, while such an adaptive sensory system exhibits a perfect adaptation property on average, its temporal stochastic fluctuations are able to be sensitive to the environmental conditions. Among the adaptive sensory systems, an extensively studied model system is the bacterial receptor responsible for chemotaxis. The model exhibits a nonadaptive fluctuation sensitive to the environmental ligand concentration, while perfect adaptation is achieved on average. Furthermore, we found that such nonadaptive fluctuation makes the bacterial behavior dependent on the environmental chemoattractant concentrations, which enhances the chemotactic performance.

Conclusions/Significance

This result indicates that adaptive sensory systems can make use of such stochastic fluctuation to carry environmental information, which is not possible by means of the average, while keeping responsive to the changing stimulus.     

Stochastic thermodynamic limit on E. coli adaptation by information geometric approach

Biological systems process information under noisy environment. Sensory adaptation model of E. coli is suitable for investigation because of its simplicity. To understand the adaptation processing quantitatively, stochastic thermodynamic approach has been attempted. Information processing can be assumed as state transition of a system that consists of signal transduction molecules using thermodynamic approach, and efficiency can be measured as thermodynamic cost. Recently, using information geometry and stochastic thermodynamics, a relationship between speed of the transition and the thermodynamic cost has been investigated for a chemical reaction model. Here, we introduce this approach to sensory adaptation model of E. coli, and examined a relationship between adaptation speed and the thermodynamic cost, and efficiency of the adaptation speed. For increasing external noise level in stimulation, the efficiency decreased, but the efficiency was highly robust to external stimulation strength. Moreover, we demonstrated that there is the best noise to achieve the adaptation in the aspect of thermodynamic efficiency. Our quantification method provides a framework to understand the adaptation speed and the thermodynamic cost for various biological systems.     

Simulating the Dynamics of Scale-Free Networks via Optimization

We deal here with the issue of complex network evolution. The analysis of topological evolution of complex networks plays a crucial role in predicting their future. While an impressive amount of work has been done on the issue, very little attention has been so far devoted to the investigation of how information theory quantifiers can be applied to characterize networks evolution. With the objective of dynamically capture the topological changes of a network''s evolution, we propose a model able to quantify and reproduce several characteristics of a given network, by using the square root of the Jensen-Shannon divergence in combination with the mean degree and the clustering coefficient. To support our hypothesis, we test the model by copying the evolution of well-known models and real systems. The results show that the methodology was able to mimic the test-networks. By using this copycat model, the user is able to analyze the networks behavior over time, and also to conjecture about the main drivers of its evolution, also providing a framework to predict its evolution.     

Daisyworld is Darwinian: constraints on adaptation are important for planetary self-regulation

The Daisyworld model demonstrates that self-regulation of the global environment can emerge from competition amongst types of life altering their local environment in different ways. Robertson & Robinson (1998. J. theor. Biol.195, 129-134) presented what they describe as a "Darwinian Daisyworld" in which the ability of organisms to adapt their internal physiology in response to environmental change undermines their ability to regulate their environment. They assume that there are no bounds on the environmental conditions that organisms can adapt to and that equal growth rates can potentially be achieved under any conditions. If adaptation could respond sufficiently rapidly to changes in the environment, this would eliminate any need for the environment to be regulated in the first place, because all possible states of the environment would be equally tolerable to life. However, the thermodynamics, chemistry and structure of living organisms set bounds on the range of environmental conditions that can be adapted to. As these bounds are approached, environmental conditions limit growth rate, and adaptations necessary for survival can also cost energy. Here we take account of such constraints and find that environmental regulation is recovered in the Daisyworld model. Hence, we suggest that constraints are an important part of a self-regulating planetary system.     

Ecological change in dynamic environments: Accounting for temporal environmental variability in studies of ocean change biology

The environmental conditions in the ocean have long been considered relatively more stable through time compared to the conditions on land. Advances in sensing technologies, however, are increasingly revealing substantial fluctuations in abiotic factors over ecologically and evolutionarily relevant timescales in the ocean, leading to a growing recognition of the dynamism of the marine environment as well as new questions about how this dynamism may influence species' vulnerability to global environmental change. In some instances, the diurnal or seasonal variability in major environmental change drivers, such as temperature, pH and seawater carbonate chemistry, and dissolved oxygen, can exceed the changes expected with continued anthropogenic global change. While ocean global change biologists have begun to experimentally test how variability in environmental conditions mediates species' responses to changes in the mean, the extensive literature on species' adaptations to temporal variability in their environment and the implications of this variability for their evolutionary responses has not been well integrated into the field. Here, we review the physiological mechanisms underlying species' responses to changes in temperature, pCO₂/pH (and other carbonate parameters), and dissolved oxygen, and discuss what is known about behavioral, plastic, and evolutionary strategies for dealing with variable environments. In addition, we discuss how exposure to variability may influence species' responses to changes in the mean conditions and highlight key research needs for ocean global change biology.     

New aspects on phosphate sensing and signalling in Saccharomyces cerevisiae

The mechanism involved in the cellular phosphate response of Saccharomyces cerevisiae forms part of the PHO pathway, which upon expression allows a co-ordinated cellular response and adaptation to changes in availability of external phosphate. Although genetic studies and analyses of the S. cerevisiae genome have produced much information on the components of the PHO pathway, little is known about how cells sense the environmental phosphate level and the mechanistic regulation of phosphate acquisition. Recent studies emphasize different levels in phosphate sensing and signalling in response to external phosphate fluctuations. This review integrates all these findings into a model involving rapid and long-term effects of phosphate sensing and signalling in S. cerevisiae. The model describes in particular how yeast cells are able to adjust phosphate acquisition by integrating the status of the intracellular phosphate pools together with the extracellular phosphate concentration.     

Sensory acquisition in active sensing systems

A defining feature of active sensing is the use of self-generated energy to probe the environment. Familiar biological examples include echolocation in bats and dolphins and active electrolocation in weakly electric fish. Organisms that utilize active sensing systems can potentially exert control over the characteristics of the probe energy, such as its intensity, direction, timing, and spectral characteristics. This is in contrast to passive sensing systems, which rely on extrinsic energy sources that are not directly controllable by the organism. The ability to control the probe energy adds a new dimension to the task of acquiring relevant information about the environment. Physical and ecological constraints confronted by active sensing systems include issues of signal propagation, attenuation, speed, energetics, and conspicuousness. These constraints influence the type of energy that organisms use to probe the environment, the amount of energy devoted to the process, and the way in which the nervous system integrates sensory and motor functions for optimizing sensory acquisition performance.     

基于斑块的红树林空间演变机理分析方法

现有红树林空间动态分析多是从整体的角度分析其面积的变化情况及其影响因素,着重于面积变化的定量分析和影响因素的定性分析,对其变化的发生途径缺乏深入分析,也不研究其斑块数量的变化动态。由于一定区域范围内的红树林由成百上千甚至更多空间上相互分离的斑块组成,各斑块边界和面积变化动态构成了区域红树林整体的空间分布变化动态,因此,只有深入摸清各个斑块的变化情况及其影响因素,才能对区域红树林整体变化情况作出全面、详细和准确的分析评估。提出了基于斑块的红树林空间演变机理分析方法,首先通过两期高空间分辨率遥感图像提取红树林空间分布信息,在GIS支持下采用叠置分析方法,根据前、后两期各个斑块的空间位置、形状和面积变化情况以及图像表征,逐一分析确定每个斑块变化的主要驱动因子(即变化原因,包括自然过程、围垦、养殖塘和盐田建设、工程建设和人工造林5种)和变化途径(即变化类型,包括稳定、扩张、萎缩、碎化、消失和新增6种),在此基础上构建斑块数量和面积变化的驱动因子-变化途径状态矩阵,通过总驱动量、总驱动率、净驱动量、净驱动率、趋势驱动率、总流量、总流率、净流量、净流率、趋势净流率和作用力等系列指标定量地评估红树林斑块数量和面积的变化动态。该方法不但能够定量地表达了各个驱动因子对红树林斑块数量和面积变化的影响程度,而且能够准确地阐明了红树林斑块数量和面积发生变化的途径,并且还能够准确地反映了每个驱动因子通过何种途径影响斑块数量和面积的变化,实现了红树林空间动态变化分析的定位化、定量化和精确化。     

Active touch sensing

Active sensing systems are purposive and information-seeking sensory systems. Active sensing usually entails sensor movement, but more fundamentally, it involves control of the sensor apparatus, in whatever manner best suits the task, so as to maximize information gain. In animals, active sensing is perhaps most evident in the modality of touch. In this theme issue, we look at active touch across a broad range of species from insects, terrestrial and marine mammals, through to humans. In addition to analysing natural touch, we also consider how engineering is beginning to exploit physical analogues of these biological systems so as to endow robots with rich tactile sensing capabilities. The different contributions show not only the varieties of active touch--antennae, whiskers and fingertips--but also their commonalities. They explore how active touch sensing has evolved in different animal lineages, how it serves to provide rapid and reliable cues for controlling ongoing behaviour, and even how it can disintegrate when our brains begin to fail. They demonstrate that research on active touch offers a means both to understand this essential and primary sensory modality, and to investigate how animals, including man, combine movement with sensing so as to make sense of, and act effectively in, the world.     

Diel Cycles in Chemosensory Behaviors of Free‐Ranging Rattlesnakes Lying in Wait for Prey

The sensory ecology of foragers is fundamentally influenced by changes in environmental conditions such as ambient light. Changes in ambient light may hinder the effectiveness of particular senses (e.g., impaired vision at night), but many predators rely on multiple sensory systems and may continue to forage despite changes in light availability. Exactly how predator behaviors and sensory systems compensate under changes in light availability in the field is not well understood. We used radio telemetry and portable video surveillance cameras to quantify the sit‐and‐wait chemosensory foraging behavior of free‐ranging red diamond (Crotalus ruber) and northern Pacific (Crotalus oreganus oreganus) rattlesnakes during day and night periods. The two most common behaviors we observed were chemosensory probes, a behavior we describe in detail for the first time, and mouth gapes. During chemosensory probes, rattlesnakes extend their head beyond their coil, explore the surrounding area while tongue‐flicking, and subsequently return to a stationary position inside their coil. Foraging rattlesnakes probed at significantly higher rates during nocturnal vs. diurnal hours. Similarly, mouth gaping occurred during a higher percentage of nocturnal vs. diurnal hours for foraging snakes. Nearly half of all mouth gapes were followed immediately with a chemosensory probe, suggesting that mouth gaping also serves a chemosensory function in this context. Our results suggest that chemical cues play an increasingly important role in mediating rattlesnake foraging behavior at night. Examining how abiotic factors, such as light availability, influence the sensory ecology of free‐ranging predators is essential for accurately characterizing their interactions with prey.     

Adaptation accentuates responses of fly motion-sensitive visual neurons to sudden stimulus changes

Adaptation in sensory and neuronal systems usually leads to reduced responses to persistent or frequently presented stimuli. In contrast to simple fatigue, adapted neurons often retain their ability to encode changes in stimulus intensity and to respond when novel stimuli appear. We investigated how the level of adaptation of a fly visual motion-sensitive neuron affects its responses to discontinuities in the stimulus, i.e. sudden brief changes in one of the stimulus parameters (velocity, contrast, grating orientation and spatial frequency). Although the neuron''s overall response decreased gradually during ongoing motion stimulation, the response transients elicited by stimulus discontinuities were preserved or even enhanced with adaptation. Moreover, the enhanced sensitivity to velocity changes by adaptation was not restricted to a certain velocity range, but was present regardless of whether the neuron was adapted to a baseline velocity below or above its steady-state velocity optimum. Our results suggest that motion adaptation helps motion-sensitive neurons to preserve their sensitivity to novel stimuli even in the presence of strong tonic stimulation, for example during self-motion.     

A Normalization Model of Attentional Modulation of Single Unit Responses

Although many studies have shown that attention to a stimulus can enhance the responses of individual cortical sensory neurons, little is known about how attention accomplishes this change in response. Here, we propose that attention-based changes in neuronal responses depend on the same response normalization mechanism that adjusts sensory responses whenever multiple stimuli are present. We have implemented a model of attention that assumes that attention works only through this normalization mechanism, and show that it can replicate key effects of attention. The model successfully explains how attention changes the gain of responses to individual stimuli and also why modulation by attention is more robust and not a simple gain change when multiple stimuli are present inside a neuron''s receptive field. Additionally, the model accounts well for physiological data that measure separately attentional modulation and sensory normalization of the responses of individual neurons in area MT in visual cortex. The proposal that attention works through a normalization mechanism sheds new light a broad range of observations on how attention alters the representation of sensory information in cerebral cortex.     

Global and Local Concerns: What Attitudes and Beliefs Motivate Farmers to Mitigate and Adapt to Climate Change?

In response to agriculture''s vulnerability and contribution to climate change, many governments are developing initiatives that promote the adoption of mitigation and adaptation practices among farmers. Since most climate policies affecting agriculture rely on voluntary efforts by individual farmers, success requires a sound understanding of the factors that motivate farmers to change practices. Recent evidence suggests that past experience with the effects of climate change and the psychological distance associated with people''s concern for global and local impacts can influence environmental behavior. Here we surveyed farmers in a representative rural county in California''s Central Valley to examine how their intention to adopt mitigation and adaptation practices is influenced by previous climate experiences and their global and local concerns about climate change. Perceived changes in water availability had significant effects on farmers'' intention to adopt mitigation and adaptation strategies, which were mediated through global and local concerns respectively. This suggests that mitigation is largely motivated by psychologically distant concerns and beliefs about climate change, while adaptation is driven by psychologically proximate concerns for local impacts. This match between attitudes and behaviors according to the psychological distance at which they are cognitively construed indicates that policy and outreach initiatives may benefit by framing climate impacts and behavioral goals concordantly; either in a global context for mitigation or a local context for adaptation.