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

Optimal stimulation protocol in a bistable synaptic consolidation model

Consolidation of synaptic changes in response to neural activity is thought to be fundamental for memory maintenance over a timescale of hours. In experiments, synaptic consolidation can be induced by repeatedly stimulating presynaptic neurons. However, the effectiveness of such protocols depends crucially on the repetition frequency of the stimulations and the mechanisms that cause this complex dependence are unknown. Here we propose a simple mathematical model that allows us to systematically study the interaction between the stimulation protocol and synaptic consolidation. We show the existence of optimal stimulation protocols for our model and, similarly to LTP experiments, the repetition frequency of the stimulation plays a crucial role in achieving consolidation. Our results show that the complex dependence of LTP on the stimulation frequency emerges naturally from a model which satisfies only minimal bistability requirements.Comment: 23 pages, 6 figure

Particle on the Innermost Stable Circular Orbit of a Rapidly Spinning Black Hole

We compute the radiation emitted by a particle on the innermost stable circular orbit of a rapidly spinning black hole both (a) analytically, working to leading order in the deviation from extremality and (b) numerically, with a new high-precision Teukolsky code. We find excellent agreement between the two methods. We confirm previous estimates of the overall scaling of the power radiated, but show that there are also small oscillations all the way to extremality. Furthermore, we reveal an intricate mode-by-mode structure in the flux to infinity, with only certain modes having the dominant scaling. The scaling of each mode is controlled by its conformal weight, a quantity that arises naturally in the representation theory of the enhanced near-horizon symmetry group. We find relationships to previous work on particles orbiting in precisely extreme Kerr, including detailed agreement of quantities computed here with conformal field theory calculations performed in the context of the Kerr/CFT correspondence.Comment: 15 pages, 4 figures, v2: reference added, minor changes, matches published versio

A multiparameter family of irreducible representations of the quantum plane and of the quantum Weyl algebra

We construct a family of irreducible representations of the quantum plane and of the quantum Weyl algebra over an arbitrary field, assuming the deformation parameter is not a root of unity. We determine when two representations in this family are isomorphic, and when they are weight representations, in the sense of Bavula.Comment: 12 pages, Section 2 has been reorganized, new material added in a new Section