Jellyfish nerve nets provide insight into the origins of nervous systems, as both their taxonomic position and their evolutionary age imply that jellyfish resemble some of the earliest neuron-bearing, actively-swimming animals. Here, we develop the first neuronal network model for the nerve nets of jellyfish. Specifically, we focus on the moon jelly Aurelia aurita and the control of its energy-efficient swimming motion. The proposed single neuron model disentangles the contributions of different currents to a spike. The network model identifies factors ensuring non-pathological activity and suggests an optimization for the transmission of signals. After modeling the jellyfish’s muscle system and its bell in a hydrodynamic environment, we explore the swimming elicited by neural activity. We find that different delays between nerve net activations lead to well-controlled, differently directed movements. Our model bridges the scales from single neurons to behavior, allowing for a comprehensive understanding of jellyfish neural control of locomotion.

-Common noise acting on a population of identical oscillators can synchronize them. We develop a description of this process which is not limited to the states close to synchrony, but provides a global picture of the evolution of the ensembles. The theory is based on the WatanabeStrogatz transformation, allowing us to obtain closed stochastic equations for the global variables. We show that on the initial stage, the order parameter grows linearly in time, while on the late stages the convergence to synchrony is exponentially fast. Furthermore, we extend the theory to nonidentical ensembles with the Lorentzian distribution of natural frequencies and determine the stationary values of the order parameter in dependence on driving noise and mismatch.Introduction. -Synchronization of oscillations by a periodic forcing is a general phenomenon observed in numerous experiments. In this setup the system follows the driving and has, in particular, the same frequency, so one often speaks on frequency entrainment. Much more nontrivial is the effect of synchronization by an external noise. Here one can also distinguish between the cases when the driven system is entrained by the noise (synchrony) and the situations when the noise is not followed (asynchrony). While the difference between these regimes can be hardly seen by observing just one responding oscillator, it becomes evident if an ensemble of identical systems driven by the same noise is observed: in the case of synchronization all the oscillators in the ensemble follow the forcing and their states thus coincide, while in the asynchronous state the states of systems remain different. This effect is therefore called synchronization by common noise [1][2][3][4][5][6]. An interesting realization of this type of synchronization is the effect of reliability of neurons [7]. Here one does not use an ensemble of identical neurons, but takes one neuron and applies the same pre-recorded noise to it several times. The synchronous case appears as a reliable respond to the forcing where all the noise-induced spikes are at the same position at all runs, while for asynchrony (antireliability) the same noise produces different spike patterns [8,9]. Synchronization by common noise was also observed in physical experiments with phase-locked loop [10]

Hippocampal sharp wave/ripple oscillations are a prominent pattern of collective activity, which consists of a strong overall increase of activity with superimposed (140 − 200 Hz) ripple oscillations. Despite its prominence and its experimentally demonstrated importance for memory consolidation, the mechanisms underlying its generation are to date not understood. Several models assume that recurrent networks of inhibitory cells alone can explain the generation and main characteristics of the ripple oscillations. Recent experiments, however, indicate that in addition to inhibitory basket cells, the pattern requires in vivo the activity of the local population of excitatory pyramidal cells. Here, we study a model for networks in the hippocampal region CA1 incorporating such a local excitatory population of pyramidal neurons. We start by investigating its ability to generate ripple oscillations using extensive simulations. Using biologically plausible parameters, we find that short pulses of external excitation triggering excitatory cell spiking are required for sharp/wave ripple generation with oscillation patterns similar to in vivo observations. Our model has plausible values for single neuron, synapse and connectivity parameters, random connectivity and no strong feedforward drive to the inhibitory population. Specifically, whereas temporally broad excitation can lead to high-frequency oscillations in the ripple range, sparse pyramidal cell activity is only obtained with pulse-like external CA3 excitation. Further simulations indicate that such short pulses could originate from dendritic spikes in the apical or basal dendrites of CA1 pyramidal cells, which are triggered by coincident spike arrivals from hippocampal region CA3. Finally we show that replay of sequences by pyramidal neurons and ripple oscillations can arise intrinsically in CA1 due to structured connectivity that gives rise to alternating excitatory pulse and inhibitory gap coding; the latter denotes phases of silence in specific basket cell groups, which induce selective disinhibition of groups of pyramidal neurons. This general mechanism for sequence generation leads to sparse pyramidal cell and dense basket cell spiking, does not rely on synfire chain-like feedforward excitation and may be relevant for other brain regions as well.

Das standige Anwachsen der naturwissenschaftlich-technischen Forschung 1aRt das Wiederfinden bekanntgemachter Forschungsergebnisse immer schwieriger werden. Die Dokumentation hat rum Ziel, diese Schwierigkeiten zu uberwinden. Je nach Art und Umfang eines Sachgebietes wird man verschiedene Wege zu seiner Dokumentation einschlagen. Methoden und Moglichkeiten einer umfassenden Dokumentation der Chemie mit ihren Grenzgebieten werden dargelegt. I ) C. L. Eernier, Correlative Indexes VI. Amer. Documentation 1 7 , *) S . R. Ranganathan, Natural, Classificatory and Machine Lan-3, S . R. Ranganathan, Postulational Approach to Faceted Classi-9 J . W. Perry u. A. Kent, Tools for Machine Literature Searching. -, 2 7 7 [ ISSO].guages, Annals of library Scl. 6 . 65 [1959].fication, Annals of library Sci. 5, 35 [1958].