No Arabic abstract
Intracellular access with high spatiotemporal resolution can enhance our understanding of how neurons or cardiomyocytes regulate and orchestrate network activity, and how this activity can be affected with pharmacology or other interventional modalities. Nanoscale devices often employ electroporation to transiently permeate the cell membrane and record intracellular potentials, which tend to decrease rapidly to extracellular potential amplitudes with time. Here, we report innovative scalable, vertical, ultra-sharp nanowire arrays that are individually addressable to enable long-term, native recordings of intracellular potentials. We report large action potential amplitudes that are indicative of intracellular access from 3D tissue-like networks of neurons and cardiomyocytes across recording days and that do not decrease to extracellular amplitudes for the duration of the recording of several minutes. Our findings are validated with cross-sectional microscopy, pharmacology, and electrical interventions. Our experiments and simulations demonstrate that individual electrical addressability of nanowires is necessary for high-fidelity intracellular electrophysiological recordings. This study advances our understanding of and control over high-quality multi-channel intracellular recordings, and paves the way toward predictive, high-throughput, and low-cost electrophysiological drug screening platforms.
We present a study on the selection of a variety of activity patterns among neurons that are connected in multiplex framework, with neurons on two layers with different functional couplings. With Hindmarsh-Rose model for the dynamics of single neurons, we analyze the possible patterns of dynamics in each layer separately, and report emergent patterns of activity like anti-phase oscillations in multi-clusters with phase regularities and enhanced amplitude and frequency with mixed mode oscillations when the connections are inhibitory. When they are multiplexed with neurons of one layer coupled with excitatory synaptic coupling and neurons of the other layer coupled with inhibitory synaptic coupling, we observe transfer or selection of interesting patterns of collective behaviour between the layers, inducing anti-phase oscillations and multi-cluster oscillations. While the revival of oscillations occurs in the layer with excitatory coupling, the transition from anti-phase to in-phase and vice versa is observed in the other layer with inhibitory synaptic coupling. We also discuss how the selection of these patterns can be controlled by tuning the intra-layer or inter-layer coupling strengths or increasing the range of non-local coupling. With one layer having electrical coupling while the other synaptic coupling of excitatory(inhibitory)type, we find in-phase(anti-phase) synchronized patterns of activity among neurons in both layers.
Most nervous systems encode information about stimuli in the responding activity of large neuronal networks. This activity often manifests itself as dynamically coordinated sequences of action potentials. Since multiple electrode recordings are now a standard tool in neuroscience research, it is important to have a measure of such network-wide behavioral coordination and information sharing, applicable to multiple neural spike train data. We propose a new statistic, informational coherence, which measures how much better one unit can be predicted by knowing the dynamical state of another. We argue informational coherence is a measure of association and shared information which is superior to traditional pairwise measures of synchronization and correlation. To find the dynamical states, we use a recently-introduced algorithm which reconstructs effective state spaces from stochastic time series. We then extend the pairwise measure to a multivariate analysis of the network by estimating the network multi-information. We illustrate our method by testing it on a detailed model of the transition from gamma to beta rhythms.
Diffusion is a fundamental phenomenon that occurs ubiquitously in nature and remains the subject of continuous research interest. Understanding diffusion is a key to understanding leaving systems. In this Chapter, I discuss diffusion of macromolecules under crowding conditions inside living cells. I describe briefly how to characterize, model and measure diffusion properties. The focus is on physics and simulations, with a particular emphasis on the effects important for crowded, biologically relevant systems.
A method for the direct patterning of electrostatic potential at the surface of hydroxyapatite is presented here. Micro-domains of surface potential have been created on hydroxyapatite coatings by a 20 keV focused electron beam with minimal alterations of surface chemistry. The success of such approach has been confirmed by Kelvin Probe Force Microscopy measurements, which show that this method is capable of creating micron sized positive and negative local electrostatic potential. The shape and potential difference of these domains were found to depend on the dose of total injected charge from the electron beam as well as the speed with which such charge is injected.
The influence of surface plasmons on the magneto-optic activity in a two-dimensional hexagonal array is addressed. The experiments were performed using hexagonal array of circular holes in a ferromagnetic Ni film. Well pronounced troughs are observed in the optical reflectivity, resulting from the presence of surface plasmons. The surface plasmons are found to strongly enhance the magneto-optic response (Kerr rotation), as compared to a continuous film of the same composition. The influence of the hexagonal symmetry of the pattern on the coupling between the plasmonic excitations is demonstrated, using optical diffraction measurements and theoretical calculations of the magneto-optic and of the angular dependence of the optical activity.