Open Data In Neurophysiology: Advancements, Solutions & Challenges.

Across the life sciences, an ongoing effort over the last 50 years has made data and methods more reproducible and transparent. This openness has led to transformative insights and vastly accelerated scientific progress. For example, structural biology and genomics have undertaken systematic collection and publication of protein sequences and structures over the past half-century, and these data have led to scientific breakthroughs that were unthinkable when data collection first began (e.

Selective Electroporation of Tumor Cells Under AC Radiofrequency Stimulation - A Numerical Study.

Self-consistent evaluations of membrane electroporation along with local heating in single spherical cells arising from external AC radiofrequency electrical stimulation have been carried out. The present numerical study seeks to determine whether healthy and malignant cells exhibit separate electroporative responses with regards to operating frequency. It is shown that cells of Burkitt's lymphoma would respond to frequencies >4.

A guide to the BRAIN Initiative Cell Census Network data ecosystem.

Characterizing cellular diversity at different levels of biological organization and across data modalities is a prerequisite to understanding the function of cell types in the brain. Classification of neurons is also essential to manipulate cell types in controlled ways and to understand their variation and vulnerability in brain disorders. The BRAIN Initiative Cell Census Network (BICCN) is an integrated network of data-generating centers, data archives, and data standards developers, with the goal of systematic multimodal brain cell type profiling and characterization.

Nonlinear stimulus representations in neural circuits with approximate excitatory-inhibitory balance.

Balanced excitation and inhibition is widely observed in cortex. How does this balance shape neural computations and stimulus representations? This question is often studied using computational models of neuronal networks in a dynamically balanced state. But balanced network models predict a linear relationship between stimuli and population responses.

Inference of synaptic connectivity and external variability in neural microcircuits.

A major goal in neuroscience is to estimate neural connectivity from large scale extracellular recordings of neural activity in vivo. This is challenging in part because any such activity is modulated by the unmeasured external synaptic input to the network, known as the common input problem. Many different measures of functional connectivity have been proposed in the literature, but their direct relationship to synaptic connectivity is often assumed or ignored.

Correlated states in balanced neuronal networks.

Understanding the magnitude and structure of interneuronal correlations and their relationship to synaptic connectivity structure is an important and difficult problem in computational neuroscience. Early studies show that neuronal network models with excitatory-inhibitory balance naturally create very weak spike train correlations, defining the "asynchronous state." Later work showed that, under some connectivity structures, balanced networks can produce larger correlations between some neuron pairs, even when the average correlation is very small.

Magnetophoretic Conductors and Diodes in a 3D Magnetic Field.

We demonstrate magnetophoretic conductor tracks that can transport single magnetized beads and magnetically labeled single cells in a 3-dimensional time-varying magnetic field. The vertical field bias, in addition to the in-plane rotating field, has the advantage of reducing the attraction between particles, which inhibits the formation of particle clusters. However, the inclusion of a vertical field requires the re-design of magnetic track geometries which can transport magnetized objects across the substrate.

Characterizing the Switching Thresholds of Magnetophoretic Transistors.

The switching thresholds of magnetophoretic transistors for sorting cells in microfluidic environments are characterized. The transistor operating conditions require short 20-30 mA pulses of electrical current. By demonstrating both attractive and repulsive transistor modes, a single transistor architecture is used to implement the full write cycle for importing and exporting single cells in specified array sites.