Highlights d Two network models of the mouse primary visual cortex are developed and released d One uses compartmental-neuron models and the other pointneuron models d The models recapitulate observations from in vivo experimental data d Simulations identify experimentally testable predictions about cortex circuitry

Biological protein pores and pore-forming peptides can generate a pathway for the flux of ions and other charged or polar molecules across cellular membranes. In nature, these nanopores have diverse and essential functions that range from maintaining cell homeostasis and participating in cell signaling to activating or killing cells. The combination of the nanoscale dimensions and sophisticated – often regulated – functionality of these biological pores make them particularly attractive for the growing field of nanobiotechnology. Applications range from single-molecule sensing to drug delivery and targeted killing of malignant cells. Potential future applications may include the use of nanopores for single strand DNA sequencing and for generating bio-inspired, and possibly, biocompatible visual detection systems and batteries. This article reviews the current state of applications of pore-forming peptides and proteins in nanomedicine, sensing, and nanoelectronics.

Synchronization over networks depends strongly on the structure of the coupling between the oscillators. When the coupling presents certain regularities, the dynamics can be coarse-grained into clusters by means of External Equitable Partitions of the network graph and their associated quotient graphs. We exploit this graph-theoretical concept to study the phenomenon of cluster synchronization, in which different groups of nodes converge to distinct behaviors. We derive conditions and properties of networks in which such clustered behavior emerges and show that the ensuing dynamics is the result of the localization of the eigenvectors of the associated graph Laplacians linked to the existence of invariant subspaces. The framework is applied to both linear and non-linear models, first for the standard case of networks with positive edges, before being generalized to the case of signed networks with both positive and negative interactions. We illustrate our results with examples of both signed and unsigned graphs for consensus dynamics and for partial synchronization of oscillator networks under the master stability function as well as Kuramoto oscillators.

33 The mammalian visual system, from retina to neocortex, has been extensively studied at both 34 anatomical and functional levels. Anatomy indicates the cortico-thalamic system is hierarchical, 35 but characterization of cellular-level functional interactions across multiple levels of this 36 hierarchy is lacking, partially due to the challenge of simultaneously recording activity across 37 numerous regions. Here, we describe a large, open dataset (part of the Allen Brain Observatory) 38 that surveys spiking from units in six cortical and two thalamic regions responding to a battery of 39 visual stimuli. Using spike cross-correlation analysis, we find that inter-area functional 40 connectivity mirrors the anatomical hierarchy from the Allen Mouse Brain Connectivity Atlas. 41Classical functional measures of hierarchy, including visual response latency, receptive field 42 size, phase-locking to a drifting grating stimulus, and autocorrelation timescale are all correlated 43 with the anatomical hierarchy. Moreover, recordings during a visual task support the behavioral 44 relevance of hierarchical processing. Overall, this dataset and the hierarchy we describe provide 45 a foundation for understanding coding and dynamics in the mouse cortico-thalamic visual 46 system. 47