How single neuron properties shape chaotic dynamics and signal transmission in random neural networks

While most models of randomly connected networks assume nodes with simple dynamics, nodes in realistic highly connected networks, such as neurons in the brain, exhibit intrinsic dynamics over multiple timescales. We analyze how the dynamical properties of nodes (such as single neurons) and recurrent connections interact to shape the effective dynamics in large randomly connected networks. A novel dynamical mean-field theory for strongly connected networks of multi-dimensional rate units shows that the power spectrum of the network activity in the chaotic phase emerges from a nonlinear sharpening of the frequency response function of single units. For the case of two-dimensional rate units with strong adaptation, we find that the network exhibits a state of "resonant chaos", characterized by robust, narrow-band stochastic oscillations. The coherence of stochastic oscillations is maximal at the onset of chaos and their correlation time scales with the adaptation timescale of single units. Surprisingly, the resonance frequency can be predicted from the properties of isolated units, even in the presence of heterogeneity in the adaptation parameters. In the presence of these internally-generated chaotic fluctuations, the transmission of weak, low-frequency signals is strongly enhanced by adaptation, whereas signal transmission is not influenced by adaptation in the non-chaotic regime. Our theoretical framework can be applied to other mechanisms at the level of single nodes, such as synaptic filtering, refractoriness or spike synchronization. These results advance our understanding of the interaction between the dynamics of single units and recurrent connectivity, which is a fundamental step toward the description of biologically realistic network models in the brain, or, more generally, networks of other physical or man-made complex dynamical units

Self-confidence and survival

We consider the impact of history on the survival of a monopolist selling single units in discrete time periods, whose quality is learned slowly. If the seller learns her own quality at the same rate as customers, a sufficiently bad run of luck could induce her to stop selling. When she knows her quality, a good seller never stops selling. Furthermore, a seller with positive, though imperfect, information sells for the same number of periods whether her information is private or public. We further consider the robustness of the central result when the seller's opportunities for strategic behaviour are limited

Formation of the postmitotic nuclear envelope from extended ER cisternae precedes nuclear pore assembly

During mitosis, the nuclear envelope merges with the endoplasmic reticulum (ER), and nuclear pore complexes are disassembled. In a current model for reassembly after mitosis, the nuclear envelope forms by a reshaping of ER tubules. For the assembly of pores, two major models have been proposed. In the insertion model, nuclear pore complexes are embedded in the nuclear envelope after their formation. In the prepore model, nucleoporins assemble on the chromatin as an intermediate nuclear pore complex before nuclear envelope formation. Using live-cell imaging and electron microscope tomography, we find that the mitotic assembly of the nuclear envelope primarily originates from ER cisternae. Moreover, the nuclear pore complexes assemble only on the already formed nuclear envelope. Indeed, all the chromatin-associated Nup 107–160 complexes are in single units instead of assembled prepores. We therefore propose that the postmitotic nuclear envelope assembles directly from ER cisternae followed by membrane-dependent insertion of nuclear pore complexes

The responses of single units to simple and complex sounds from the superior olivary complex of the Guinea pig

© 2018 The Author(s). We have recorded the responses of single units in the superior olivary complex (SOC) of the Guinea pig to simple and complex stimuli. We can readily identify the responses of the four principal ascending nuclei as described in other species and we are therefore confident that the Guinea pig is a suitable model for studying this region. We found single units in the medial superior olive that represent both diotic iterated rippled noise and dichotic repetition pitch in their temporal discharge patterns. Our data demonstrate a use of the SOC beyond sound-source localisation

Multiple Single-Unit Long-Term Tracking on Organotypic Hippocampal Slices Using High-Density Microelectrode Arrays

A novel system to cultivate and record from organotypic brain slices directly on high-density microelectrode arrays (HD-MEA) was developed. This system allows for continuous recording of electrical activity of specific individual neurons at high spatial resolution while monitoring at the same time, neuronal network activity. For the first time, the electrical activity patterns of single neurons and the corresponding neuronal network in an organotypic hippocampal slice culture were studied during several consecutive weeks at daily intervals. An unsupervised iterative spike-sorting algorithm, based on PCA and k-means clustering, was developed to assign the activities to the single units. Spike-triggered average extracellular waveforms of an action potential recorded across neighboring electrodes, termed ‘footprints’ of single-units were generated and tracked over weeks. The developed system offers the potential to study chronic impacts of drugs or genetic modifications on individual neurons in slice preparations over extended times