A theory of hippocampal memory based on theta phase precession

 The neural dynamics of the hippocampal network for memory encoding of novel temporal sequences is proposed based on the theta rhythm modulated firing of place cells called theta phase precession. It is hypothesized that theta phase precession is generated at the entorhinal cortex by phase locking between local field theta oscillation and neural oscillators and that the hippocampal closed network with feedforward and backward projections employ theta phase precession to create selectivity in the associative connections needed for temporal sequence storage. Our analyses and computer experiments reveal that the phase precession generated by phase locking instantaneously endows stable phase relations among neural activities in the successively changing neural population. It is concluded that theta phase precession provides biologically plausible dynamics for the memory encoding of novel temporal sequences as episodic events. Received: 18 December 2002 / Accepted: 18 March 2003 / Published online: 20 May 2003 Correspondence to: Y. Yamaguchi (e-mail: yokoy@brain.riken.go.jp, Fax: +81-48-4676938) Acknowledgements. The author would like to express acknowledgement to Drs. McNaughton and Skaggs for their discussion and comment and to Dr. Amari for his continuous encouragement. Further thanks are given to Mr. Haga and Dr. Wu for their discussion and cooperation.     

Neural computations in the tiger salamander and mudpuppy outer retinae and an analysis of GABA action from horizontal cells

 A neural network architecture based on the neural anatomy and function of retinal neurons in tiger salamander and mudpuppy retinae is proposed to study basic aspects of early visual information processing. The model predictions for the main response characteristics of retinal neurons are found to be in agreement with neurophysiological data, including the antagonistic role of horizontal cells in the outer plexiform layer. The examination of possible γ-aminobutyric acid (GABA) action from horizontal cells suggests that GABA_A alone, GABA_B alone, or their weighted combination can generate the response characteristics observed in bipolar cells. Received: 25 June 2002 / Accepted: 28 January 2003 / Published online: 20 May 2003 Acknowledgements. The authors would like to thank an anonymous reviewer for valuable comments. Correspondence to: S. X. Yang (e-mail: syang@uoguelph.ca)     

Emergence of coherent traveling waves controlling quadruped gaits in a two-dimensional spinal cord model

 The concerted and self-organizing behavior of spinal cord segments in generating locomotor patterns is modulated by afferent sensory information and controlled by descending pathways from the brainstem, cerebellum, or cortex. The purpose of this study was to define a minimal set of parameters that could control a similar self-organizing behavior in a two-dimensional neural network. When we implemented synaptic depression and active membrane repolarization as two properties of the neurons, the two-dimensional neural network generated traveling waves. Their wavelength and angle of propagation could be independently controlled by two parameters that modulated excitatory premotor neurons and inhibitory commissural neurons. It is further demonstrated that the selection of wave parameters corresponds to the selection of quadruped gaits. Received: 30 July 2001 / Accepted in revised form: 17 April 2002 Correspondence to: A. Kaske (e-mail: alexander.kaske@mtc.ki.se, alexander.kaske@vglab.com)     

Deriving physical connectivity from neuronal morphology

 A model is presented that allows prediction of the probability for the formation of appositions between the axons and dendrites of any two neurons based only on their morphological statistics and relative separation. Statistics of axonal and dendritic morphologies of single neurons are obtained from 3D reconstructions of biocytin-filled cells, and a statistical representation of the same cell type is obtained by averaging across neurons according to the model. A simple mathematical formulation is applied to the axonal and dendritic statistical representations to yield the probability for close appositions. The model is validated by a mathematical proof and by comparison of predicted appositions made by layer 5 pyramidal neurons in the rat somatosensory cortex with real anatomical data. The model could be useful for studying microcircuit connectivity and for designing artificial neural networks. Received: 11 February 2002 / Accepted: 5 November 2002 / Published online: 20 February 2003 Correspondence to: H. Markram (e-mail: Henry.Markram@epfl.ch Tel.: +41-21-6939537, Fax: +41-21-6935350) Acknowledgements. This study was supported by the National Alliance for Autism Research, the Minerva Foundation, the US Navy, the Ebner Center for Biomedical Research, and the Edith Blum Foundation.     

Changing excitation and inhibition in simulated neural networks: effects on induced bursting behavior

 The development of synchronous bursting in neuronal ensembles represents an important change in network behavior. To determine the influences on development of such synchronous bursting behavior we study the dynamics of small networks of sparsely connected excitatory and inhibitory neurons using numerical simulations. The synchronized bursting activities in networks evoked by background spikes are investigated. Specifically, patterns of bursting activity are examined when the balance between excitation and inhibition on neuronal inputs is varied and the fraction of inhibitory neurons in the network is changed. For quantitative comparison of bursting activities in networks, measures of the degree of synchrony are used. We demonstrate how changes in the strength of excitation on inputs of neurons can be compensated by changes in the strength of inhibition without changing the degree of synchrony in the network. The effects of changing several network parameters on the network activity are analyzed and discussed. These changes may underlie the transition of network activity from normal to potentially pathologic (e.g., epileptic) states. Received: 21 May 2002 / Accepted in revised form: 3 December 2002 / Published online: 7 March 2003 Correspondence to: P. Kudela (e-mail: pkudela@jhmi.edu) Acknowledgements. This research was supported by NIH grant NS 38958.     

Resonance tuning in a neuro-musculo-skeletal model of the forearm

In rhythmic movements, humans activate their muscles in a robust and energy efficient way. These activation patterns are oscillatory and seem to originate from neural networks in the spinal cord, called central pattern generators (CPGs). Evidence for the existence of CPGs was found for instance in lampreys, cats and rats. There are indications that CPGs exist in humans as well, but this is not proven yet. Energy efficiency is achieved by resonance tuning: the central nervous system is able to tune into the resonance frequency of the limb, which is determined by the local reflex gains. The goal of this study is to investigate if the existence of a CPG in the human spine can explain the resonance tuning behavior, observed in human rhythmic limb movement. A neuro-musculo-skeletal model of the forearm is proposed, in which a CPG is organized in parallel to the local reflexloop. The afferent and efferent connections to the CPG are based on clues about the organization of the CPG, found in literature. The model is kept as simple as possible (i.e., lumped muscle models, groups of neurons are lumped into half-centers, simple reflex model), but incorporates enough of the essential dynamics to explain behavior—such as resonance tuning—in a qualitative way. Resonance tuning is achieved above, at and below the endogenous frequency of the CPG in a highly non-linear neuro- musculo-skeletal model. Afferent feedback of muscle lengthening to the CPG is necessary to accomplish resonance tuning above the endogenous frequency of the CPG, while feedback of muscle velocity is necessary to compensate for the phase lag, caused by the time delay in the loop coupling the limb to the CPG. This afferent feedback of muscle lengthening and velocity represents the Ia and II fibers, which—according to literature—is the input to the CPG. An internal process of the CPG, which integrates the delayed muscle lengthening and feeds it to the half-center model, provides resonance tuning below the endogenous frequency. Increased co-contraction makes higher movement frequencies possible. This agrees with studies of rhythmic forearm movements, which have shown that co-contraction increases with movement frequency. Robustness against force perturbations originates mainly from the CPG and the local reflex loop. The CPG delivers an increasing part of the necessary muscle activation for increasing perturbation size. As far as we know, the proposed neuro-musculo-skeletal model is the first that explains the observed resonance tuning in human rhythmic limb movement.     

Modeling of a bipedal locomotor using coupled nonlinear oscillators of Van der Pol

 Research to date points to an understanding of human biped locomotion that has been primarily experimental in nature largely due to the complexity of the process. In view of the new, exciting possibilities of programmed electrostimulation of artificial muscles to generate motion (locomotion), a critical study at the theoretical level is greatly warranted. There is strong evidence that many biological clocks consist of a population of mutually coupled oscillators [Pavlidis T (1973) Biological oscillators, Academic; Johnsson A (1978) Zur Biophysik biologischer Oszillatoren. In: Biophisik, Springer]. In this work, a form of bipedal locomotion is simulated by using mutually coupled nonlinear oscillators. A planar model, which includes three out of the six determinants of gait that characterize the human locomotion, was adopted. Received: 4 August 2002 / Accepted: 12 November 2002 / Published online: 7 March 2003 Correspondence to: M. S. Dutra (e-mail: max@serv.com.ufrj.br) Acknowledgements. The authors would like to express their gratitude to CNPq, CAPES, and FAPERJ for the financial support provided during the course of this research.     

The role of postinhibitory rebound in the locomotor central-pattern generator of Clione limacina

In animals, networks of central neurons, called central-patterngenerators (CPGs), produce a variety of locomotory behaviorsincluding walking, swimming, and flying. CPGs from diverse animalsshare many common characteristics that function at the systemlevel, circuit level, and cellular level. However, the relativeroles of common CPG characteristics are variable among differentanimal species, in ways that suit different forms of locomotionin different environmental contexts. Here, we examine some ofthese common features within the locomotor CPG in a model systemused to investigate changes in locomotory speed—the swimsystem of the pteropod mollusk, Clione limacina. In particular,we discuss the role of one cellular characteristic that is essentialfor locomotor pattern generation in Clione, postinhibitory rebound.     

<Emphasis Type="Italic">Umbelopsis gibberispora</Emphasis> sp. nov. from Japanese leaf litter and a clarification of <Emphasis Type="Italic">Micromucor ramannianus </Emphasis>var. <Emphasis Type="Italic">angulisporus</Emphasis>

 Umbelopsis gibberispora is described as a new species in the genus Umbelopsis, Umbelopsidaceae, Mucorales. The species differs from others in this genus by ellipsoidal sporangiospores with unilaterally thickened walls. Phylogenetic analyses based on nuclear large subunit ribosomal DNA (nLSU rDNA) partial sequences suggest that U. gibberispora, U. swartii, and U. westeae form a clade together with the strains of Umbelopsis ramanniana. The ex-type strain of Micromucor ramannianus var. angulisporus is found to be very close to Umbelopsis vinacea, whereas other isolates identified under the former name in the sense of Linnemann fall in the U. ramanniana subclade. For these isolates, a new species, Umbelopsis angularis, is introduced. Phylogenetic relationships among Umbelopsis species are discussed related to their attributes of the sporangial wall and mature spore shapes. Received: August 27, 2002 / Accepted: March 11, 2003 Acknowledgments We thank Dr. Takashi Ohsono, Graduate School of Agriculture, Kyoto University, Japan, for providing the strain of U. gibberispora (CBS 109328). We also thank Dr. Wieland Meyer, University of Sydney, Australia for access to the phylogenetic tree based on ITS sequence data before publishing, and Dr. Richard C. Summerbell, Centraalbureau von Schimmelcultures, the Netherlands, for linguistic corrections.     

Pleosporales in Japan (3). The genus Massarina

 Twelve species of the genus Massarina collected from Japan are reported in this article. Among them, 4 new species, M. constricta, M. japonica, M. submediana, and M. uniserialis, are described, illustrated, and compared to similar species. Two species, M. scirpina and M. ryukyuensis, are described as new combination, and 4 species, M. arundinariae, M. fluviatilis, M. peerallyi, and M. rubi, are reported from Japan for the first time. One bambusicolous species, Metasphaeria tuberculosa, is considered to be a synonym of Massarina bambusina. Received: December 13, 2002 / Accepted: February 6, 2003 Acknowledgments We are grateful to Dr. Shuhei Tanaka, curator of YAM (Yamaguchi University), for the loan of specimens for this study.     

Dissolved organic carbon and fluorescence in Lake Hovsgol: factors reducing humic content of the lake water

 Lake Hovsgol is a large tectonic lake located in northern Mongolia, which has extremely transparent lake water. In our survey, the dissolved organic carbon of the lake water was 80–100 μM-C, and the fluorescence intensity in an excitation and emission matrix was very low. The brown color and high content of humic substances in river water flowing from a watershed consisting of grassland and forests rapidly declined in the coastal area of the lake. The decrease in humic content may be due not only to dilution by the lake water but also to flocculation and photobleaching. Among tectonic lakes in Asia, Lake Hovsgol would appear to have unique biological and hydrological features that reduce humic content and help to maintain water transparency. Received: June 25, 2002 / Accepted: January 10, 2003 Acknowledgments The authors acknowledge helpful discussion with Dr. J. Urabe. We thank Dr. T. Galbaatar, Mongolian Academy of Science, Mongolia, for his arrangements on the expeditions in 1999. We are also indebted to Mr. D. Hadbaatar, B. Ganbat, and the cruise staff of the R/V Suchbaatar for their assistance in the course of the study. This study was supported by Grant-in-Aid No. 09041159 and 13575034 for Scientific Research from the Ministry of Education, Culture, Sports, Science and Technology of Japan. Correspondence to:K. Hayakawa     

Metabolic interactions between restraint stress and <Emphasis Type="SmallCaps">l</Emphasis>-lysine: The effect on urea cycle components

Summary.  We studied the effects of l-lysine on wrap-restraint stress-induced changes in ureagenesis. An exposure to wrap-restraint stress did not affect the plasma concentration of l-lysine, but did decrease plasma urea and arginine. Oral l-lysine (1 g/kg) blocked the effect of stress on ureagenesis, and enhanced the effect of stress on l-arginine. No influence of l-lysine were found in controls. The results imply a stress-specific, ureagenesis-stimulating effect of l-lysine, and suggest an increased requirement for l-arginine during the above conditions. Received December 9, 2002 Accepted January 21, 2003 Published online April 3, 2003 Acknowledgement Authors thank Dr. M. Miura (Ajinomoto Co.) for his help with amino acid analysis and Dr. T. Kimura (Ajinomoto Co.) for discussions on amino acid metabolism. Authors' address: Dr. M. Smriga, Ajinomoto Co. Inc., Institute of Life Sciences, 1-1 Suzuki-cho, 210-8681 Kawasaki, Japan, Fax +81-44-210-5893, E-mail: miroslav_smriga@ajinomoto.com Abbreviations: Arg, l-arginine; Orn, l-ornithine; Lys, l-lysine; p.o., oral; WRS, wrap-restraint stress     

A ternary logic model for recurrent neuromime networks with delay

 In contrast to popular recurrent artificial neural network (RANN) models, biological neural networks have unsymmetric structures and incorporate significant delays as a result of axonal propagation. Consequently, biologically inspired neural network models are more accurately described by nonlinear differential-delay equations rather than nonlinear ordinary differential equations (ODEs), and the standard techniques for studying the dynamics of RANNs are wholly inadequate for these models. This paper develops a ternary-logic based method for analyzing these networks. Key to the technique is the realization that a nonzero delay produces a bounded stability region. This result significantly simplifies the construction of sufficient conditions for characterizing the network equilibria. If the network gain is large enough, each equilibrium can be classified as either asymptotically stable or unstable. To illustrate the analysis technique, the swim central pattern generator (CPG) of the sea slug Tritonia diomedea is examined. For wide range of reasonable parameter values, the ternary analysis shows that none of the network equilibria are stable, and thus the network must oscillate. The results show that complex synaptic dynamics are not necessary for pattern generation. Received: 15 June 1994/Accepted in revised form: 10 February 1995     

Multiple motor patterns in the stomatogastric ganglion of the shrimp Penaeus japonicus

 Motor patterns of the cardiac sac, the gastric and the pyloric network in the stomatogastric nervous system of the shrimp Penaeus japonicus, the most primitive decapod species, were studied. Single neurons can switch from the gastric or the pyloric pattern to the cardiac sac pattern. Some of the pyloric neurons fire with the gastric pattern. All of the gastric neurons fire with the pyloric pattern, unlike those in reptantians. Proctolin activates and modulates the cardiac sac and the pyloric rhythm, and promotes reconfiguration of the networks. Neurons of the three networks have so many interconnections that they construct a multifunctional neural network like those in Cancer. This network may function in different configurations under the appropriate conditions. Several modes of interactions between the networks found in different reptantian species can apply to the penaeidean shrimp. Such interactions are general features of the stomatogastric nervous system in decapods. Phylogenetic differences among the decapod infraorders are seen in the number and orientation of muscles and the innervation pattern of muscles. The multifunctional networks have existed in the most primitive decapod species, and types of configurations of the networks would have evolved to produce a wide range of motor patterns as the foregut structure has become complex. Accepted: 26 October 1999     

Modeling of the pyruvate production with Escherichia coli: comparison of mechanistic and neural networks-based models

Three different models: the unstructured mechanistic black-box model, the input–output neural network-based model and the externally recurrent neural network model were used to describe the pyruvate production process from glucose and acetate using the genetically modified Escherichia coli YYC202 ldhA::Kan strain. The experimental data were used from the recently described batch and fed-batch experiments [ Zelić B, Study of the process development for Escherichia coli-based pyruvate production. PhD Thesis, University of Zagreb, Faculty of Chemical Engineering and Technology, Zagreb, Croatia, July 2003. (In English); Zelić et al. Bioproc Biosyst Eng 26:249–258 (2004); Zelić et al. Eng Life Sci 3:299–305 (2003); Zelić et al Biotechnol Bioeng 85:638–646 (2004)]. The neural networks were built out of the experimental data obtained in the fed-batch pyruvate production experiments with the constant glucose feed rate. The model validation was performed using the experimental results obtained from the batch and fed-batch pyruvate production experiments with the constant acetate feed rate. Dynamics of the substrate and product concentration changes was estimated using two neural network-based models for biomass and pyruvate. It was shown that neural networks could be used for the modeling of complex microbial fermentation processes, even in conditions in which mechanistic unstructured models cannot be applied.     

Analysis of higher-order neuronal interactions based on conditional inference

 Higher-order neural interactions, i.e., interactions that cannot be reduced to interactions between pairs of cells, have received increasing attention in the context of recent attempts to understand the cooperative dynamics in cortical neural networks. Typically, likelihood-ratio tests of log-linear models are being employed for statistical inference. The parameter estimation of these models for simultaneously recorded single-neuron spiking activities is a crucial ingredient of this approach. Extending a previous investigation of a two-neuron system, we present here the general formulation of an exact test suited for the detection of positive higher-order interactions between m neurons. This procedure does not require the estimation of any interaction parameters and additionally optimizes the test power of the statistical inference. We apply the approach to a three-neuron system and show how second-order and third-order interactions can be reliably distinguished. We study the performance of the method as a function of the interaction strength. Received: 18 January 2002 / Accepted in revised form: 26 November 2002 / Published online: 13 March 2003 RID="*" ID="*" Present address: Institute for Theoretical Biology, Humboldt University, 10115 Berlin, Germany Correspondence to: R. Gütig (e-mail: r.guetig@biologie.hu-berlin.de, Tel.: +49 30 2093 9112, Fax: +49 30 2093 8801) Acknowledgements. We thank Shun-ichi Amari and Hiro Nakahara for valuable discussions on the information geometry of the exponential family of probability distributions underlying the present approach. Supported in part by the Studienstiftung des deutschen Volkes, the German-Israeli Foundation for Scientific Research and Development (GIF), the Deutsche Forschungsgemeinschaft (DFG), and the Institut für Grenzgebiete der Psychologie, Freiburg.     

An in silico central pattern generator: silicon oscillator,coupling, entrainment,and physical computation

 In biological systems, the task of computing a gait trajectory is shared between the biomechanical and nervous systems. We take the perspective that both of these seemingly different computations are examples of physical computation. Here we describe the progress that has been made toward building a minimal biped system that illustrates this idea. We embed a significant portion of the computation in physical devices, such as capacitors and transistors, to underline the potential power of emphasizing the understanding of physical computation. We describe results in the exploitation of physical computation by (1) using a passive knee to assist in dynamics computation, (2) using an oscillator to drive a monoped mechanism based on the passive knee, (3) using sensory entrainment to coordinate the mechanics with the neural oscillator, (4) coupling two such systems together mechanically at the hip and computationally via the resulting two oscillators to create a biped mechanism, and (5) demonstrating the resulting gait generation in the biped mechanism. Received: 31 October 2001 / Accepted in revised form: 17 September 2002 Correspondence to: M.A. Lewis     

New species of <Emphasis Type="Italic">Clitocybe </Emphasis>and <Emphasis Type="Italic">Crepidotus </Emphasis>(Agaricales) from eastern Honshu,Japan

 Three new species of Agaricales from eastern Honshu, Japan, are described and illustrated. (1) Clitocybe minutella sp. nov. (section Vernae), having white, very small, clitocyboid basidiomata with white, strigose mycelial tomentum at the base of the stipe and trichodermial elements in the pileipellis, occurs on leaf litter in deciduous oak forests. (2) Crepidotus longicomatus sp.nov. (section Echinospori), forms very small (up to 3.5 mm in diameter), reniform basidiomata densely covered overall with white to pale yellow, erect, thick-walled, long hairs. It has melleous, echinulate basidiospores, and was found on fallen dead branches in lowland oak forests. (3) Crepidotus virgineus sp. nov. (section Crepidotus), forming pure white, reniform basidiomata, has smooth, ellipsoid basidiospores, subfusiform-pedicellate to irregularly cylindrical cheilocystidia, and abundant clamp connections. It occurs on fallen dead branches in lowland oak forests. Received: August 22, 2002 / Accepted: January 8, 2003 Acknowledgments I am grateful to Dr. Yousuke Degawa (KPM) for allowing the specimens cited to be kept in the Kanagawa Prefectural Museum of Natural History. Correspondence to:H. Takahashi     

Coherency and connectivity in oscillating neural networks: linear partialization analysis

 This paper studies the relation between the functional synaptic connections between two artificial neural networks and the correlation of their spiking activities. The model neurons had realistic non-oscillatory dynamic properties and the networks showed oscillatory behavior as a result of their internal synaptic connectivity. We found that both excitation and inhibition cause phase locking of the oscillating activities. When the two networks excite each other the oscillations synchronize with zero phase lag, whereas mutual inhibition between the networks resulted in an anti-phase (half period phase difference) synchronization. Correlations between the activities of the two networks can also be caused by correlated external inputs driving the systems (common input). Our analysis shows that when the networks exhibit oscillatory behavior and the rate of the common input is smaller than a characteristic network oscillator frequency, the cross-correlation functions between the activities of two systems still carry information about the mutual synaptic connectivity. This information can be retrieved with linear partialization, removing the influence of the common input. We further explored the network responses to periodic external input. We found that when the input is of a frequency smaller than a certain threshold, the network responds with bursts at the same frequency as the input. Above the threshold, the network responds with a fraction of the input frequency. This frequency threshold, characterizing the oscillatory properties of the network, is also found to determine the limit to which linear partialization works. Received: 20 October 1995 / Accepted in revised form: 20 May 1996