Ilya Kolb

Microchip amplifier for in vitro, in vivo, and automated whole cell patch-clamp recording.

Patch clamping is a gold-standard electrophysiology technique that has the temporal resolution and signal-to-noise ratio capable of reporting single ion channel currents, as well as electrical activity of excitable single cells. Despite its usefulness and decades of development, the amplifiers required for patch clamping are expensive and bulky. This has limited the scalability and throughput of patch clamping for single-ion channel and single-cell analyses. In this work, we have developed a custom patch-clamp amplifier microchip that can be fabricated using standard commercial silicon processes capable of performing both voltage- and current-clamp measurements. A key innovation is the use of nonlinear feedback elements in the voltage-clamp amplifier circuit to convert measured currents into logarithmically encoded voltages, thereby eliminating the need for large high-valued resistors, a factor that has limited previous attempts at integration. Benchtop characterization of the chip shows low levels of current noise [1.1 pA root mean square (rms) over 5 kHz] during voltage-clamp measurements and low levels of voltage noise (8.2 μV rms over 10 kHz) during current-clamp measurements. We demonstrate the ability of the chip to perform both current- and voltage-clamp measurement in vitro in HEK293FT cells and cultured neurons. We also demonstrate its ability to perform in vivo recordings as part of a robotic patch-clamping system. The performance of the patch-clamp amplifier microchip compares favorably with much larger commercial instrumentation, enabling benchtop commoditization, miniaturization, and scalable patch-clamp instrumentation.

Cleaning patch-clamp pipettes for immediate reuse

Patch-clamp recording has enabled single-cell electrical, morphological and genetic studies at unparalleled resolution. Yet it remains a laborious and low-throughput technique, making it largely impractical for large-scale measurements such as cell type and connectivity characterization of neurons in the brain. Specifically, the technique is critically limited by the ubiquitous practice of manually replacing patch-clamp pipettes after each recording. To circumvent this limitation, we developed a simple, fast, and automated method for cleaning glass pipette electrodes that enables their reuse within one minute. By immersing pipette tips into Alconox, a commercially-available detergent, followed by rinsing, we were able to reuse pipettes 10 times with no degradation in signal fidelity, in experimental preparations ranging from human embryonic kidney cells to neurons in culture, slices, and in vivo. Undetectable trace amounts of Alconox remaining in the pipette after cleaning did not affect ion channel pharmacology. We demonstrate the utility of pipette cleaning by developing the first robot to perform sequential patch-clamp recordings in cell culture and in vivo without a human operator.

Robotic navigation to subcortical neural tissue for intracellular electrophysiology in vivo

In vivo studies of neurophysiology using the whole cell patch-clamp technique enable exquisite access to both intracellular dynamics and cytosol of cells in the living brain but are underrepresented in deep subcortical nuclei because of fouling of the sensitive electrode tip. We have developed an autonomous method to navigate electrodes around obstacles such as blood vessels after identifying them as a source of contamination during regional pipette localization (RPL) in vivo. In mice, robotic navigation prevented fouling of the electrode tip, increasing RPL success probability 3 mm below the pial surface to 82% (n = 72/88) over traditional, linear localization (25%, n = 24/95), and resulted in high-quality thalamic whole cell recordings with average access resistance (32.0 MΩ) and resting membrane potential (-62.9 mV) similar to cortical recordings in isoflurane-anesthetized mice. Whole cell yield improved from 1% (n = 1/95) to 10% (n = 9/88) when robotic navigation was used during RPL. This method opens the door to whole cell studies in deep subcortical nuclei, including multimodal cell typing and studies of long-range circuits.NEW & NOTEWORTHY This work represents an automated method for accessing subcortical neural tissue for intracellular electrophysiology in vivo. We have implemented a novel algorithm to detect obstructions during regional pipette localization and move around them while minimizing lateral displacement within brain tissue. This approach leverages computer control of pressure, manipulator position, and impedance measurements to create a closed-loop platform for pipette navigation in vivo. This technique enables whole cell patching studies to be performed throughout the living brain.

Cell Membrane Tracking in Living Brain Tissue Using Differential Interference Contrast Microscopy

Differential interference contrast (DIC) microscopy is widely used for observing unstained biological samples that are otherwise optically transparent. Combining this optical technique with machine vision could enable the automation of many life science experiments; however, identifying relevant features under DIC is challenging. In particular, precise tracking of cell boundaries in a thick (

Evidence for long-timescale patterns of synaptic inputs in CA1 of awake behaving mice

{>} 100 \mu \text{m}

Integration of autopatching with automated pipette and cell detection in vitro

) slice of tissue has not previously been accomplished. We present a novel deconvolution algorithm that achieves the state-of-the-art performance at identifying and tracking these membrane locations. Our proposed algorithm is formulated as a regularized least squares optimization that incorporates a filtering mechanism to handle organic tissue interference and a robust edge-sparsity regularizer that integrates dynamic edge tracking capabilities. As a secondary contribution, this paper also describes new community infrastructure in the form of a MATLAB toolbox for accurately simulating DIC microscopy images of in vitro brain slices. Building on existing DIC optics modeling, our simulation framework additionally contributes an accurate representation of interference from organic tissue, neuronal cell-shapes, and tissue motion due to the action of the pipette. This simulator allows us to better understand the image statistics (to improve algorithms), as well as quantitatively test cell segmentation and tracking algorithms in scenarios, where ground truth data is fully known.

Automated, in-vivo, whole-cell electrophysiology using an integrated patch-clamp amplifier.

Repeated sequences of neural activity are a pervasive feature of neural networks in vivo and in vitro. In the hippocampus, sequential firing of many neurons over periods of 100–300 ms reoccurs during behavior and during periods of quiescence. However, it is not known whether the hippocampus produces longer sequences of activity or whether such sequences are restricted to specific network states. Furthermore, whether long repeated patterns of activity are transmitted to single cells downstream is unclear. To answer these questions, we recorded intracellularly from hippocampal CA1 of awake, behaving male mice to examine both subthreshold activity and spiking output in single neurons. In eight of nine recordings, we discovered long (900 ms) reoccurring subthreshold fluctuations or “repeats.” Repeats generally were high-amplitude, nonoscillatory events reoccurring with 10 ms precision. Using statistical controls, we determined that repeats occurred more often than would be expected from unstructured network activity (e.g., by chance). Most spikes occurred during a repeat, and when a repeat contained a spike, the spike reoccurred with precision on the order of ≤20 ms, showing that long repeated patterns of subthreshold activity are strongly connected to spike output. Unexpectedly, we found that repeats occurred independently of classic hippocampal network states like theta oscillations or sharp-wave ripples. Together, these results reveal surprisingly long patterns of repeated activity in the hippocampal network that occur nonstochastically, are transmitted to single downstream neurons, and strongly shape their output. This suggests that the timescale of information transmission in the hippocampal network is much longer than previously thought. SIGNIFICANCE STATEMENT We found long (≥900 ms), repeated, subthreshold patterns of activity in CA1 of awake, behaving mice. These repeated patterns (“repeats”) occurred more often than expected by chance and with 10 ms precision. Most spikes occurred within repeats and reoccurred with a precision on the order of 20 ms. Surprisingly, there was no correlation between repeat occurrence and classical network states such as theta oscillations and sharp-wave ripples. These results provide strong evidence that long patterns of activity are repeated and transmitted to downstream neurons, suggesting that the hippocampus can generate longer sequences of repeated activity than previously thought.