Short-term memory capacity in networks via the restricted isometry property.

Cortical networks are hypothesized to rely on transient network activity to support short-term memory (STM). In this letter, we study the capacity of randomly connected recurrent linear networks for performing STM when the input signals are approximately sparse in some basis. We leverage results from compressed sensing to provide rigorous nonasymptotic recovery guarantees, quantifying the impact of the input sparsity level, the input sparsity basis, and the network characteristics on the system capacity. Our analysis demonstrates that network memory capacities can scale superlinearly with the number of nodes and in some situations can achieve STM capacities that are much larger than the network size. We provide perfect recovery guarantees for finite sequences and recovery bounds for infinite sequences. The latter analysis predicts that network STM systems may have an optimal recovery length that balances errors due to omission and recall mistakes. Furthermore, we show that the conditions yielding optimal STM capacity can be embodied in several network topologies, including networks with sparse or dense connectivities.

Immune surveillance by mast cells during dengue infection promotes natural killer (NK) and NKT-cell recruitment and viral clearance.

A wealth of evidence supports the essential contributions of mast cells (MCs) to immune defense against bacteria and parasites; however, the role of MCs in viral infections has not been defined. We now report that rodent, monkey, and human MCs are able to detect dengue virus (DENV), a lymphotropic, enveloped, single-stranded, positive-sense RNA virus that results in MC activation and degranulation. We observe that the response of MCs to DENV also involves the activation of antiviral intracellular host response pathways, melanoma differentiation-associated gene 5 (MDA5) and retinoic acid inducible gene 1 (RIG-I), and the de novo transcription of cytokines, including TNF-α and IFN-α, and chemokines, such as CCL5, CXCL12, and CX3CL1. This multifaceted response of MCs to DENV is consequential to the containment of DENV in vivo because, after s.c. infection, MC-deficient mice show increased viral burden within draining lymph nodes, which are known to be targeted organs during DENV spread, compared with MC-sufficient mice. This containment of DENV is linked to the MC-driven recruitment of natural killer and natural killer T cells into the infected skin. These findings support expanding the defined role of immunosurveillance by MCs to include viral pathogens.

Stabilizing embedology: Geometry-preserving delay-coordinate maps.

Delay-coordinate mapping is an effective and widely used technique for reconstructing and analyzing the dynamics of a nonlinear system based on time-series outputs. The efficacy of delay-coordinate mapping has long been supported by Takens' embedding theorem, which guarantees that delay-coordinate maps use the time-series output to provide a reconstruction of the hidden state space that is a one-to-one embedding of the system's attractor. While this topological guarantee ensures that distinct points in the reconstruction correspond to distinct points in the original state space, it does not characterize the quality of this embedding or illuminate how the specific parameters affect the reconstruction. In this paper, we extend Takens' result by establishing conditions under which delay-coordinate mapping is guaranteed to provide a stable embedding of a system's attractor. Beyond only preserving the attractor topology, a stable embedding preserves the attractor geometry by ensuring that distances between points in the state space are approximately preserved. In particular, we find that delay-coordinate mapping stably embeds an attractor of a dynamical system if the stable rank of the system is large enough to be proportional to the dimension of the attractor. The stable rank reflects the relation between the sampling interval and the number of delays in delay-coordinate mapping. Our theoretical findings give guidance to choosing system parameters, echoing the tradeoff between irrelevancy and redundancy that has been heuristically investigated in the literature. Our initial result is stated for attractors that are smooth submanifolds of Euclidean space, with extensions provided for the case of strange attractors.

Radiative heat transfer as a Landauer-Büttiker problem.

We study the radiative heat transfer between two semi-infinite half-spaces, bounded by conductive surfaces in contact with vacuum. This setup is interpreted as a four-terminal mesoscopic transport problem. The slabs and interfaces are viewed as bosonic reservoirs, coupled perfectly to a scattering center consisting of the two planes and vacuum. Using Rytov's fluctuational electrodynamics and assuming Kirchhoff's circuital law, we calculate the heat flow in each bath. This allows for explicit evaluation of a conductance matrix, from which one readily verifies Büttiker symmetry. Thus, radiative heat transfer in layered media with conductive interfaces becomes a Landauer-Büttiker transport problem.