Scalable Measurements of Intrinsic Excitability in Human iPS Cell-Derived Excitatory Neurons Using All-Optical Electrophysiology.

Induced pluripotent stem (iPS) cells offer the exciting opportunity for modeling neurological disorders in vitro in the context of a human genetic background. While significant progress has been made in advancing the use of iPS cell-based disease models, there remains an unmet need to characterize the electrophysiological profile of individual neurons with sufficient throughput to enable statistically robust assessment of disease phenotypes and pharmacological modulation. Here, we describe the Optopatch platform technology that utilizes optogenetics to both stimulate and record action potentials (APs) from human iPS cell-derived excitatory neurons with similar information content to manual patch clamp electrophysiology, but with ~  3 orders of magnitude greater throughput. Cortical excitatory neurons were produced using the NGN2 transcriptional programming approach and cultured in the presence of rodent glial cells. Characterization of the neuronal preparations using immunocytochemistry and qRT-PCR assays reveals an enrichment of neuronal and glutamatergic markers as well as select ion channels. We demonstrate the scale of our intrinsic cellular excitability assay using pharmacological assessment with select ion channel modulators quinidine and retigabine, by measuring changes in both spike timing and waveform properties. The Optopatch platform in human iPS cell-derived cortical excitatory neurons has the potential for detailed phenotype and pharmacology evaluation, which can serve as the basis of cellular disease model exploration for drug discovery and phenotypic screening efforts.

Dry friction avalanches: experiment and theory.

Experimental evidence and theoretical models are presented supporting the conjecture that dry friction stick-slip is described by self-organized criticality. We use the data, obtained with a pin-on-disk tribometer set to measure lateral force, to examine the variation of the friction force as a function of time. We study nominally flat surfaces of matching aluminum and steel. The probability distribution of force drops follows a negative power law with exponents mu in the range 3.2-3.5. The frequency power spectrum follows a 1/f alpha pattern with alpha in the range 1-1.8. We first compare these experimental results with the well-known Robin Hood model of self-organized criticality. We find good agreement between theory and experiment for the force-drop distribution but not for the power spectrum. We explain this on a physical basis and propose a model which takes explicitly into account the stiffness and inertia of the tribometer. Specifically, we numerically solve the equation of motion of a block on a friction surface pulled by a spring and show that for certain spring constants the motion is characterized by the same power law spectrum as in experiments. We propose a physical picture relating the fluctuations of the force drops to the microscopic geometry of the surface.