Complexity without chaos: Plasticity within random recurrent networks generates robust timing and motor control

It is widely accepted that the complex dynamics characteristic of recurrent neural circuits contributes in a fundamental manner to brain function. Progress has been slow in understanding and exploiting the computational power of recurrent dynamics for two main reasons: nonlinear recurrent networks often exhibit chaotic behavior and most known learning rules do not work in robust fashion in recurrent networks. Here we address both these problems by demonstrating how random recurrent networks (RRN) that initially exhibit chaotic dynamics can be tuned through a supervised learning rule to generate locally stable neural patterns of activity that are both complex and robust to noise. The outcome is a novel neural network regime that exhibits both transiently stable and chaotic trajectories. We further show that the recurrent learning rule dramatically increases the ability of RRNs to generate complex spatiotemporal motor patterns, and accounts for recent experimental data showing a decrease in neural variability in response to stimulus onset

Balanced Input Allows Optimal Encoding in a Stochastic Binary Neural Network Model: An Analytical Study

Recent neurophysiological experiments have demonstrated a remarkable effect of attention on the underlying neural activity that suggests for the first time that information encoding is indeed actively influenced by attention. Single cell recordings show that attention reduces both the neural variability and correlations in the attended condition with respect to the non-attended one. This reduction of variability and redundancy enhances the information associated with the detection and further processing of the attended stimulus. Beyond the attentional paradigm, the local activity in a neural circuit can be modulated in a number of ways, leading to the general question of understanding how the activity of such circuits is sensitive to these relatively small modulations. Here, using an analytically tractable neural network model, we demonstrate how this enhancement of information emerges when excitatory and inhibitory synaptic currents are balanced. In particular, we show that the network encoding sensitivity -as measured by the Fisher information- is maximized at the exact balance. Furthermore, we find a similar result for a more realistic spiking neural network model. As the regime of balanced inputs has been experimentally observed, these results suggest that this regime is functionally important from an information encoding standpoint

Generating Single Microwave Photons in a Circuit

Electromagnetic signals in circuits consist of discrete photons, though conventional voltage sources can only generate classical fields with a coherent superposition of many different photon numbers. While these classical signals can control and measure bits in a quantum computer (qubits), single photons can carry quantum information, enabling non-local quantum interactions, an important resource for scalable quantum computing. Here, we demonstrate an on-chip single photon source in a circuit quantum electrodynamics (QED) architecture, with a microwave transmission line cavity that collects the spontaneous emission of a single superconducting qubit with high efficiency. The photon source is triggered by a qubit rotation, as a photon is generated only when the qubit is excited. Tomography of both qubit and fluorescence photon shows that arbitrary qubit states can be mapped onto the photon state, demonstrating an ability to convert a stationary qubit into a flying qubit. Both the average power and voltage of the photon source are characterized to verify performance of the system. This single photon source is an important addition to a rapidly growing toolbox for quantum optics on a chip.Comment: 6 pages, 5 figures, hires version at http://www.eng.yale.edu/rslab/papers/single_photon_hires.pd

Neural Network Mechanisms Underlying Stimulus Driven Variability Reduction

It is well established that the variability of the neural activity across trials, as measured by the Fano factor, is elevated. This fact poses limits on information encoding by the neural activity. However, a series of recent neurophysiological experiments have changed this traditional view. Single cell recordings across a variety of species, brain areas, brain states and stimulus conditions demonstrate a remarkable reduction of the neural variability when an external stimulation is applied and when attention is allocated towards a stimulus within a neuron's receptive field, suggesting an enhancement of information encoding. Using an heterogeneously connected neural network model whose dynamics exhibits multiple attractors, we demonstrate here how this variability reduction can arise from a network effect. In the spontaneous state, we show that the high degree of neural variability is mainly due to fluctuation-driven excursions from attractor to attractor. This occurs when, in the parameter space, the network working point is around the bifurcation allowing multistable attractors. The application of an external excitatory drive by stimulation or attention stabilizes one specific attractor, eliminating in this way the transitions between the different attractors and resulting in a net decrease in neural variability over trials. Importantly, non-responsive neurons also exhibit a reduction of variability. Finally, this reduced variability is found to arise from an increased regularity of the neural spike trains. In conclusion, these results suggest that the variability reduction under stimulation and attention is a property of neural circuits

A state-of-the-art review of curve squeal noise: Phenomena, mechanisms, modelling and mitigation

[EN] Curve squeal is an intense tonal noise occurring when a rail vehicle negotiates a sharp curve. The phenomenon can be considered to be chaotic, with a widely differing likelihood of occurrence on different days or even times of day. The term curve squeal may include several different phenomena with a wide range of dominant frequencies and potentially different excitation mechanisms. This review addresses the different squeal phenomena and the approaches used to model squeal noise; both time-domain and frequency-domain approaches are discussed and compared. Supporting measurements using test rigs and field tests are also summarised. A particular aspect that is addressed is the excitation mechanism. Two mechanisms have mainly been considered in previous publications. In many early papers the squeal was supposed to be generated by the so-called falling friction characteristic in which the friction coefficient reduces with increasing sliding velocity. More recently the mode coupling mechanism has been raised as an alternative. These two mechanisms are explained and compared and the evidence for each is discussed. Finally, a short review is given of mitigation measures and some suggestions are offered for why these are not always successful.Squicciarini, G.; Thompson, D.; Ding, B.; Baeza González, LM. (2018). A state-of-the-art review of curve squeal noise: Phenomena, mechanisms, modelling and mitigation. Notes on Numerical Fluid Mechanics and Multidisciplinary Design. 139:3-41. https://doi.org/10.1007/978-3-319-73411-8_1S341139Anderson, D., Wheatley, N., Fogarty, B., Jiang, J., Howie, A., Potter, W.: Mitigation of curve squeal noise in Queensland, New South Wales and South Australia. In: Conference on Railway Engineering. pp. 625–636, Perth, Australia (2008)Hanson, D., Jiang, J., Dowdell, B., Dwight, R.: Curve squeal: causes, treatments and results. 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Springer, Heidelberg (2015)Zenzerovic, I., Kropp, W., Pieringer, A.: An engineering time-domain model for curve squeal: tangential point-contact model and Green’s functions approach. J. Sound Vib. 376, 149–165 (2016)Pieringer, A., Torstensson, P.T., Giner, J., Baeza, L.: Investigation of railway curve squeal using a combination of frequency- and time-domain models. In: Anderson, D., et al. (eds.) Noise and Vibration Mitigation for Rail Transportation Systems. NNFM, vol. 139, pp 81–93. Springer, Heidelberg (2018)Chen, G.X., Xiao, J.B., Liu, Q.Y., Zhou. Z.R.: Complex eigenvalue analysis of railway curve squeal. In: Schulte-Werning, B., et al. (eds.) Noise and Vibration Mitigation for Rail Transportation Systems. NNFM, vol. 99, pp. 433–439. Springer, Heidelberg (2008)Fourie, D.J., Gräbe, P.J., Heyns, P.S., Fröhling, R.D.: Analysis of wheel squeal due to unsteady longitudinal creepage using the complex eigenvalue method. In: Anderson, D., et al. (eds.) 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Dynamic Effective Connectivity of Inter-Areal Brain Circuits

Anatomic connections between brain areas affect information flow between neuronal circuits and the synchronization of neuronal activity. However, such structural connectivity does not coincide with effective connectivity (or, more precisely, causal connectivity), related to the elusive question “Which areas cause the present activity of which others?”. Effective connectivity is directed and depends flexibly on contexts and tasks. Here we show that dynamic effective connectivity can emerge from transitions in the collective organization of coherent neural activity. Integrating simulation and semi-analytic approaches, we study mesoscale network motifs of interacting cortical areas, modeled as large random networks of spiking neurons or as simple rate units. Through a causal analysis of time-series of model neural activity, we show that different dynamical states generated by a same structural connectivity motif correspond to distinct effective connectivity motifs. Such effective motifs can display a dominant directionality, due to spontaneous symmetry breaking and effective entrainment between local brain rhythms, although all connections in the considered structural motifs are reciprocal. We show then that transitions between effective connectivity configurations (like, for instance, reversal in the direction of inter-areal interactions) can be triggered reliably by brief perturbation inputs, properly timed with respect to an ongoing local oscillation, without the need for plastic synaptic changes. Finally, we analyze how the information encoded in spiking patterns of a local neuronal population is propagated across a fixed structural connectivity motif, demonstrating that changes in the active effective connectivity regulate both the efficiency and the directionality of information transfer. Previous studies stressed the role played by coherent oscillations in establishing efficient communication between distant areas. Going beyond these early proposals, we advance here that dynamic interactions between brain rhythms provide as well the basis for the self-organized control of this “communication-through-coherence”, making thus possible a fast “on-demand” reconfiguration of global information routing modalities

Coordinately Regulated Alternative Splicing of Genes Involved in Cholesterol Biosynthesis and Uptake

Genes involved in cholesterol biosynthesis and uptake are transcriptionally regulated in response to cellular sterol content in a coordinated manner. A number of these genes, including 3-hydroxy-3-methylglutaryl coenzyme A reductase (HMGCR) and LDL receptor (LDLR), undergo alternative splicing, resulting in reductions of enzyme or protein activity. Here we demonstrate that cellular sterol depletion suppresses, and sterol loading induces, alternative splicing of multiple genes involved in the maintenance of cholesterol homeostasis including HMGCR and LDLR, the key regulators of cellular cholesterol biosynthesis and uptake, respectively. These changes were observed in both in vitro studies of the HepG2 human hepatoma derived cell line, as well as in vivo studies of St. Kitts vervets, also known as African green monkeys, a commonly used primate model for investigating cholesterol metabolism. These effects are mediated in part by sterol regulation of polypyrimidine tract binding protein 1 (PTBP1), since knock-down of PTBP1 eliminates sterol induced changes in alternative splicing of several of these genes. Single nucleotide polymorphisms (SNPs) that influence HMGCR and LDLR alternative splicing (rs3846662 and rs688, respectively), have been associated with variation in plasma LDL-cholesterol levels. Sterol-induced changes in alternative splicing are blunted in carriers of the minor alleles for each of these SNPs, indicating an interaction between genetic and non-genetic regulation of this process. Our results implicate alternative splicing as a novel mechanism of enhancing the robust transcriptional response to conditions of cellular cholesterol depletion or accumulation. Thus coordinated regulation of alternative splicing may contribute to cellular cholesterol homeostasis as well as plasma LDL levels

Sensory Stimulation-Dependent Plasticity in the Cerebellar Cortex of Alert Mice

In vitro studies have supported the occurrence of cerebellar long-term depression (LTD), an interaction between the parallel fibers and Purkinje cells (PCs) that requires the combined activation of the parallel and climbing fibers. To demonstrate the existence of LTD in alert animals, we investigated the plasticity of local field potentials (LFPs) evoked by electrical stimulation of the whisker pad. The recorded LFP showed two major negative waves corresponding to trigeminal (broken into the N2 and N3 components) and cortical responses. PC unitary extracellular recording showed that N2 and N3 occurred concurrently with PC evoked simple spikes, followed by an evoked complex spike. Polarity inversion of the N3 component at the PC level and N3 amplitude reduction after electrical stimulation of the parallel fiber volley applied on the surface of the cerebellum 2 ms earlier strongly suggest that N3 was related to the parallel fiber–PC synapse activity. LFP measurements elicited by single whisker pad stimulus were performed before and after trains of electrical stimuli given at a frequency of 8 Hz for 10 min. We demonstrated that during this later situation, the stimulation of the PC by parallel and climbing fibers was reinforced. After 8-Hz stimulation, we observed long-term modifications (lasting at least 30 min) characterized by a specific decrease of the N3 amplitude accompanied by an increase of the N2 and N3 latency peaks. These plastic modifications indicated the existence of cerebellar LTD in alert animals involving both timing and synaptic modulations. These results corroborate the idea that LTD may underlie basic physiological functions related to calcium-dependent synaptic plasticity in the cerebellum

Control of Cerebellar Long-Term Potentiation by P-Rex-Family Guanine-Nucleotide Exchange Factors and Phosphoinositide 3-Kinase

Long-term potentiation (LTP) at the parallel fibre-Purkinje cell synapse in the cerebellum is a recently described and poorly characterized form of synaptic plasticity. The induction mechanism for LTP at this synapse is considered reciprocal to "classical" LTP at hippocampal CA1 pyramidal neurons: kinases promote increased trafficking of AMPA receptors into the postsynaptic density in the hippocampus, whereas phosphatases decrease internalization of AMPA receptors in the cerebellum. In the hippocampus, LTP occurs in overlapping phases, with the transition from early to late phases requiring the consolidation of initial induction processes by structural re-arrangements at the synapse. Many signalling pathways have been implicated in this process, including PI3 kinases and Rho GTPases.We hypothesized that analogous phases are present in cerebellar LTP, and took as the starting point for investigation our recent discovery that P-Rex--a Rac guanine nucleotide exchange factor which is activated by PtdIns(3,4,5)P(3)--is highly expressed in mouse cerebellar Purkinje neurons and plays a role in motor coordination. We found that LTP evoked at parallel fibre synapses by 1 Hz stimulation or by NO donors was not sustained beyond 30 min when P-Rex was eliminated or Rac inhibited, suggesting that cerebellar LTP exhibits a late phase analogous to hippocampal LTP. In contrast, inhibition of PI3 kinase activity eliminated LTP at the induction stage.Our data suggest that a PI3K/P-Rex/Rac pathway is required for late phase LTP in the mouse cerebellum, and that other PI3K targets, which remain to be discovered, control LTP induction