Here we describe a new deep atomic force microscope (AFM) capable of ion sensing. A novel probe assembly incorporates a micropipette that can be used both for sensing ion currents and as the tip for AFM imaging. The key advance of this instrument over previous ion sensing AFMs is that it uses conventional micropipettes in a novel suspension system. This paper focuses on sensing the ion current passively while using force feedback for the operation of the AFM in contact mode. Two images are obtained simultaneously: (1) an AFM topography image and (2) an ion current image. As an example, two images of a MEMS device with a microchannel show peaks in the ion current as the pipette tip goes over the edges of the channel. This ion sensing AFM can also be used in other modes including tapping mode with force feedback as well as in non-contact mode by utilizing the ion current for feedback, as in scanning ion conductance microscopy. The instrument is gentle enough to be used on some biological samples such as plant leaves.

We developed a method to non-invasively detect synaptic relationships among neurons from in vitro networks. Our method uses microelectrode arrays on which neurons are cultured and from which propagation of extracellular action potentials (eAPs) in single axons are recorded at multiple electrodes. Detecting eAP propagation bypasses ambiguity introduced by spike sorting. Our methods identify short latency spiking relationships between neurons with properties expected of synaptically coupled neurons, namely they were recapitulated by direct stimulation and were sensitive to changing the number of active synaptic sites. Our methods enabled us to assemble a functional subset of neuronal connectivity in our cultures.

Multi-electrode arrays (MEAs) can record extracellular action potentials (also known as 'spikes') from hundreds or thousands of neurons simultaneously. Inference of a functional network from a spike train is a fundamental and formidable computational task in neuroscience. With the advancement of MEA technology, it has become increasingly crucial to develop statistical tools for analyzing multiple neuronal activity as a network. In this paper, we propose a scalable Bayesian framework for inference of functional networks from MEA data. Our framework makes use of the hierarchical structure of networks of neurons. We split the large scale recordings into smaller local networks for network inference, which not only eases the computational burden from Bayesian sampling but also provides useful insights on regional connections in organoids and brains. We speed up the expensive Bayesian sampling process by using parallel computing. Experiments on both synthetic datasets and large-scale real-world MEA recordings show the effectiveness and efficiency of the scalable Bayesian framework. Inference of networks from controlled experiments exposing neural cultures to cadmium presents distinguishable results and further confirms the utility of our framework.

Action potentials can be recorded extracellularly from hundreds of neurons simultaneously with multi-electrode arrays. These can typically have as many as 120 or more electrodes. The brief duration of action potentials requires a high sampling frequency to reliably capture each waveform. The resulting raw data files are therefore large and difficult to visualize with traditional plotting tools. Common approaches to deal with the difficulties of data display, such as extracting spike times and performing spike train analysis, are useful in many contexts but they also significantly reduce data dimensionality. The use of tools which minimize data processing enable the development of heuristic perspective of experimental results. Here we introduce MEA Viewer, a high-performance open source application for the direct visualization of multi-channel electrophysiological data. MEA Viewer includes several high-performance visualizations, including an easily navigable overview of recorded extracellular action potentials from all data channels overlaid with spike timestamp data and an interactive raster plot. MEA Viewer can also display the two dimensional extent of action potential propagation in single neurons by signal averaging extracellular action potentials (eAPs) from single neurons detected on multiple electrodes. This view extracts and displays eAP timing information and eAP waveforms that are otherwise below the spike detection threshold. This entirely new method of using MEAs opens up novel research applications for medium density arrays. MEA Viewer is licensed under the General Public License version 3, GPLv3, and is available at http://github.com/dbridges/mea-tools.

Bone tissue mechanical properties are deemed a key component of bone strength, but their assessment requires invasive procedures. Here we validate a new instrument, a reference point indentation (RPI) instrument, for measuring these tissue properties in vivo. The RPI instrument performs bone microindentation testing (BMT) by inserting a probe assembly through the skin covering the tibia and, after displacing periosteum, applying 20 indentation cycles at 2 Hz each with a maximum force of 11 N. We assessed 27 women with osteoporosis-related fractures and 8 controls of comparable ages. Measured total indentation distance (46.0 +/- 14 versus 31.7 +/- 3.3 microm, p = .008) and indentation distance increase (18.1 +/- 5.6 versus 12.3 +/- 2.9 microm, p = .008) were significantly greater in fracture patients than in controls. Areas under the receiver operating characteristic (ROC) curve for the two measurements were 93.1% (95% confidence interval [CI] 83.1-100) and 90.3% (95% CI 73.2-100), respectively. Interobserver coefficient of variation ranged from 8.7% to 15.5%, and the procedure was well tolerated. In a separate study of cadaveric human bone samples (n = 5), crack growth toughness and indentation distance increase correlated (r = -0.9036, p = .018), and scanning electron microscope images of cracks induced by indentation and by experimental fractures were similar. We conclude that BMT, by inducing microscopic fractures, directly measures bone mechanical properties at the tissue level. The technique is feasible for use in clinics with good reproducibility. It discriminates precisely between patients with and without fragility fracture and may provide clinicians and researchers with a direct in vivo measurement of bone tissue resistance to fracture.

A novel, hand-held Reference Point Indentation (RPI) instrument, measures how well the bone of living patients and large animals resists indentation. The results presented here are reported in terms of Bone Material Strength, which is a normalized measure of how well the bone resists indentation, and is inversely related to the indentation distance into the bone. We present examples of the instrument's use in: (1) laboratory experiments on bone, including experiments through a layer of soft tissue, (2) three human clinical trials, two ongoing in Barcelona and at the Mayo Clinic, and one completed in Portland, OR, and (3) two ongoing horse clinical trials, one at Purdue University and another at Alamo Pintado Stables in California. The instrument is capable of measuring consistent values when testing through soft tissue such as skin and periosteum, and does so handheld, an improvement over previous Reference Point Indentation instruments. Measurements conducted on horses showed reproducible results when testing the horse through tissue or on bare bone. In the human clinical trials, reasonable and consistent values were obtained, suggesting the Osteoprobe^® is capable of measuring Bone Material Strength in vivo, but larger studies are needed to determine the efficacy of the instrument's use in medical diagnosis.

Human brain organoids replicate much of the cellular diversity and developmental anatomy of the human brain. However, the physiology of neuronal circuits within organoids remains under-explored. With high-density CMOS microelectrode arrays and shank electrodes, we captured spontaneous extracellular activity from brain organoids derived from human induced pluripotent stem cells. We inferred functional connectivity from spike timing, revealing a large number of weak connections within a skeleton of significantly fewer strong connections. A benzodiazepine increased the uniformity of firing patterns and decreased the relative fraction of weakly connected edges. Our analysis of the local field potential demonstrate that brain organoids contain neuronal assemblies of sufficient size and functional connectivity to co-activate and generate field potentials from their collective transmembrane currents that phase-lock to spiking activity. These results point to the potential of brain organoids for the study of neuropsychiatric diseases, drug action, and the effects of external stimuli upon neuronal networks.