Synaptic interactions among neurons that coordinate swimmeret and abdominal movements in the crayfish

1. Many interneurons in the crayfish (Procambarus clarkii) abdominal nervous system influence two behaviors, abdominal positioning and swimmeret movements. Such neurons are referred to as dual output cells. Other neurons which influence either one behavior or the other are single output cells. 2. Extensive synaptic interactions were observed between both dual and single output neurons involved in the control of abdominal positioning and swimmeret movements. Over 60% of all neuron pairs examined displayed interactions. Pairs of agonist neurons displayed excitatory interactions, while pairs of antagonists had inhibitory interactions. This pattern of interaction was observed in about 75% of interactive neuron pairs whether abdominal positioning or swimmeret outputs were considered. 3. Evidence for both serial and parallel connectivity, as well as, reciprocal or looping connections was observed. Looping connections can be found both between the abdominal positioning and swimmeret systems and within each system. 4. Most (28/34) single output neurons were not presynaptic to dual output neurons. No single output neurons were found to excite dual output neurons to spiking, although inhibitory interactions and weak excitations were observed. 5. Abdominal positioning inhibitors displayed properties consistent with a role in mediating some of the coordination between the swimmeret and abdominal positioning systems. 6. None of the dual output neurons examined influenced the swimmeret motoneurons directly.     

Population structure,spite, and the iterated Prisoner's Dilemma

Evolutionary stability (sensu Maynard Smith: Evolution and the Theory of Games, Cambridge: Cambridge University Press, 1982) of TIT FOR TAT (TFT) under the social ecology of the iterated Prisoner's Dilemma is a function of the number of pure TFT groups (dyads) in the population, relative to the social position of a focal invading defector. Defecting against TFT always raises the defector's relative intragroup fitness; when Axelrod's (Am. Polit. Sci. Rev. 75:306–318, 1981; The Evolution of Cooperation. New York: Basic Books, 1984) Evolutionary stable strategy (ESS) conditions are met, defection also lowers the absolute fitness of the defector. Here the retaliatory (punishing) character of TFT converts defection into spite, permitting pure TFT groups to sufficiently outproduce the defector for the latter's evolutionary suppression. Increasing the relative impact of spiteful defection on a population lowers the range of evolutionary stability for TFT. When individuals participate in multiple dyads, those participating in the greatest number of dyads are most likely to provide a vehicle for the successful invasion of defection. Within social networks, ESS conditions for TFT are thus individual specific. This logic is generalized to the context of an interated n-person Prisoner's Dilemma, providing a cooperative solution conceptually identical with TFT in the two-person game.     

Voiceprint identification and its application to sociological studies of wild Japanese monkeys (Macaca fuscata yakui)

Japanese monkeys often exchange the particular vocal sound, “coo,” especially when they feed or move as a group. It was considered that the “coo” sound had no positive social meaning, perhaps because the “coo” sound network and its function were hidden behind other behavioral observations. For identification of the vocalizer only from hearing the “coo” sound, three phonetic values, i.e., the “fundamental,” “duration,” and “formants,” plus other characteristics were used as indices of voiceprints. The results indicated that these were effective for identifying the vocalizer in two-thirds of the adults in the study troop which was composed of 12 adults and 16 immature members. The “coo” sound exchange network among the troop members (adults) was drawn on the basis of the voiceprint identification. The network showed three characteristics as follows: (1) matriarchs of the kin-groups frequently exchanged “coo” sounds with each other; (2) the other females exchanged “coo” sounds mostly within their own kin-groups; and (3) males seldom participated in the “coo” sound exchange. This suggests that “coo” sound exchange plays a central role for the matriarch of kin-groups in binding each kin-group and, ultimately, in binding all members together into an organized troop.     

Rapid authentication of animal cell lines using pyrolysis mass spectrometry and auto-associative artificial neural networks

Summary Pyrolysis mass spectrometry (PyMS) was used to produce biochemical fingerprints from replicate frozen cell cultures of mouse macrophage hybridoma 2C11-12, human leukaemia K562, baby hamster kidney BHK 21/C13, and mouse tumour BW-O, and a fresh culture of Chinese hamster ovary CHO cells. The dimensionality of these data was reduced by the unsupervised feature extraction pattern recognition technique of auto-associative neural networks. The clusters observed were compared with the groups obtained from the more conventional statistical approaches of hierarchical cluster analysis. It was observed that frozen and fresh cell line cultures gave very different pyrolysis mass spectra. When only the frozen animal cells were analysed by PyMS, auto-associative artificial neural networks (ANNs) were employed to discriminate between them successfully. Furthermore, very similar classifications were observed when the same spectral data were analysed using hierarchical cluster analysis. We demonstrate that this approach can detect the contamination of cell lines with low numbers of bacteria and fungi; this approach could plausibly be extended for the rapid detection of mycoplasma infection in animal cell lines. The major advantages that PyMS offers over more conventional methods used to type cell lines and to screen for microbial infection, such as DNA fingerprinting, are its speed, sensitivity and the ability to analyse hundreds of samples per day. We conclude that the combination of PyMS and ANNs can provide a rapid and accurate discriminatory technique for the authentication of animal cell line cultures.     

Simple models for trail-following behaviour; Trunk trails versus individual foragers

Social insects such as ants use trial-marking and trail-following to organize the behaviour and movement patterns of a large population. Since behaviour has to meet needs of the population in a changing environment, the type of trail networks formed must be adaptable. Both solitary foraging as well as mass migration along a system of trunk trails are behaviours essential for survival of the colony, and the population must be able to switch from one behaviour to the other, depending on conditions. Using a mathematical model for trail following we show that subtle changes in individual behaviour can give rise to dramatic differences in the behaviour of the population, including the ability to switch from solitary movement to organized group traffic. The model incorporates biological parameters associated with the organism, the trail-marker, and the population. Ordinary differential equations are formulated for the density of the trails and for the number of individuals following trails or exploring randomly. It is assumed that the followers reinforce trails by pheromone marking, and that individuals respond to the strength of the trails by becoming more efficient followers. The model is analyzed by qualitative phase-plane methods.     

Rapid screening for metabolite overproduction in fermentor broths, using pyrolysis mass spectrometry with multivariate calibration and artificial neural networks

Binary mixtures of model systems consisting of the antibiotic ampicillin with either Escherichia coli or Staphylococcus auresu were subjected to pyrolysis mass spectrometry (PyMS). To deconvolute the pyrolysis mass spectra, so as to obtain quantitative information on the concentration of ampicilin in the mixtures, partial least squares regression (PLS), principal components regression (PCR), and fully interconnected feedforward artificial neural networks (ANNs) were studied. In the latter case, the weights were modified using the standard backpropagation algorithm, and the nodes used a sigmoidal squsahing funciton. It was found that each of the methods could be used to provide calibration models which gave excellent predictions for the concentrations of ampicillin in samples on which they had not been trained. Furthermore, ANNs trained to predict the amount of ampicilin in E. coli were able to generalise so as to predict the concentration of ampicillin in a S. aureus background, illustrating the robustness of ANNs to rather substantial variations in the biological background. The PyMS of the complex mixture of ampicilin in bacteria could not be expressed simply in terms of additive combinations of the spectra describing the pure components of the mixtures and their relative concentrations. Intermolecular reactions took place in the pyrolysate, leading to a lack of superposition of the spectral components and to a dependence of the normalized mass spectrum on sample size. Samples from fermentations of a single organism in a complex production medium were also analyzed quantitatively for a drug of commercial interest. The drug could also be quantified in a variety of mutant-producing strains cultivated in the same medium. The combination of PyMS and ANNs constitutes a novel, rapid, and convenient method for exploitation in strain improvement screening programs. (c) 1994 John Wiley & Sons, Inc.     

厌氧消化过程的非模型控制

对废水淤泥的厌氧消化处理过程进行了研究．提出了一种基于神经网络的非模型控制方法。多变量控制系统的操作变量为供热量和进水量．被控变量为消化温度和消化污泥排出浓度。证明了控制算法的收敛性。讨论了控制系统的稳定性。仿真结果证实了非模型控制方法的有效性。该方法无需对象的模型．为复杂生化过程的控制提供了一种新途径。     

Five fundamental ways in which complex food webs may spiral out of control

Theory suggests that increasingly long, negative feedback loops of many interacting species may destabilize food webs as complexity increases. Less attention has, however, been paid to the specific ways in which these ‘delayed negative feedbacks’ may affect the response of complex ecosystems to global environmental change. Here, we describe five fundamental ways in which these feedbacks might pave the way for abrupt, large-scale transitions and species losses. By combining topological and bioenergetic models, we then proceed by showing that the likelihood of such transitions increases with the number of interacting species and/or when the combined effects of stabilizing network patterns approach the minimum required for stable coexistence. Our findings thus shift the question from the classical question of what makes complex, unaltered ecosystems stable to whether the effects of, known and unknown, stabilizing food-web patterns are sufficient to prevent abrupt, large-scale transitions under global environmental change.