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Manipulation of Single Neural Stem Cells and Neurons in Brain Slices using Robotic Microinjection

A central question in developmental neurobiology is how neural stem and progenitor cells form the brain. To answer this question, one needs to label, ...

University of Minnesota

Patch clamp is the main technique for measuring electrical properties of individual cells. Since its discovery in 1976 by Neher and Sakmann, patch clamp has been instrumental in broadening our understanding of the fundamental properties of ion channels and synapses in neurons. The conventional patch-clamp method requires manual, precise positioning of a glass micropipette against the cell membrane of a visually identified target neuron. Subsequently, a tight "gigaseal" connection between the pipette and the cell membrane is established, and suction is applied to establish the whole cell patch configuration to perform electrophysiological recordings. This procedure is repeated manually for each individual cell, making it labor intensive and time consuming. In this article we describe the development of a new automatic patch-clamp system for brain slices, which integrates all steps of the patch-clamp process: image acquisition through a microscope, computer vision-based identification of a patch pipette and fluorescently labeled neurons, micromanipulator control, and automated patching. We validated our system in brain slices from wild-type and transgenic mice expressing channelrhodopsin 2 under the Thy1 promoter (line 18) or injected with a herpes simplex virus-expressing archaerhodopsin, ArchT. Our computer vision-based algorithm makes the fluorescent cell detection and targeting user independent. Compared with manual patching, our system is superior in both success rate and average trial duration. It provides more reliable trial-to-trial control of the patching process and improves reproducibility of experiments.

Integration of autopatching with automated pipette and cell detection in vitro.

Seconds-scale network states, affecting many neurons within a network, modulate neural activity by complementing fast integration of neuron-specific inputs that arrive in the milliseconds before spiking. Nonrhythmic subthreshold dynamics at intermediate timescales, however, are less well characterized. We found, using automated whole cell patch clamping in vivo, that spikes recorded in CA1 and barrel cortex in awake mice are often preceded not only by monotonic voltage rises lasting milliseconds but also by more gradual (lasting tens to hundreds of milliseconds) depolarizations. The latter exert a gating function on spiking, in a fashion that depends on the gradual rise duration: the probability of spiking was higher for longer gradual rises, even when controlled for the amplitude of the gradual rises. Barrel cortex double-autopatch recordings show that gradual rises are shared across some, but not all, neurons. The gradual rises may represent a new kind of state, intermediate both in timescale and in proportion of neurons participating, which gates a neuron's ability to respond to subsequent inputs. We analyzed subthreshold activity preceding spikes in hippocampus and barrel cortex of awake mice. Aperiodic voltage ramps extending over tens to hundreds of milliseconds consistently precede and facilitate spikes, in a manner dependent on both their amplitude and their duration. These voltage ramps represent a "mesoscale" activated state that gates spike production in vivo.

Mesoscale-duration activated states gate spiking in response to fast rises in membrane voltage in the awake brain.

We report a noninvasive strategy for electrically stimulating neurons at depth. By delivering to the brain multiple electric fields at frequencies too high to recruit neural firing, but which differ by a frequency within the dynamic range of neural firing, we can electrically stimulate neurons throughout a region where interference between the multiple fields results in a prominent electric field envelope modulated at the difference frequency. We validated this temporal interference (TI) concept via modeling and physics experiments, and verified that neurons in the living mouse brain could follow the electric field envelope. We demonstrate the utility of TI stimulation by stimulating neurons in the hippocampus of living mice without recruiting neurons of the overlying cortex. Finally, we show that by altering the currents delivered to a set of immobile electrodes, we can steerably evoke different motor patterns in living mice.

Noninvasive Deep Brain Stimulation via Temporally Interfering Electric Fields.

Repeated sequences of neural activity are a pervasive feature of neural networks  and  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. 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.

Evidence for Long-Timescale Patterns of Synaptic Inputs in CA1 of Awake Behaving Mice.

Much innovation is currently aimed at improving the number, density, and geometry of electrodes on extracellular multielectrode arrays for in vivo recording of neural activity in the mammalian brain. To choose a multielectrode array configuration for a given neuroscience purpose, or to reveal design principles of future multielectrode arrays, it would be useful to have a systematic way of evaluating the spike recording capability of such arrays. We describe an automated system that performs robotic patch-clamp recording of a neuron being simultaneously recorded via an extracellular multielectrode array. By recording a patch-clamp data set from a neuron while acquiring extracellular recordings from the same neuron, we can evaluate how well the extracellular multielectrode array captures the spiking information from that neuron. To demonstrate the utility of our system, we show that it can provide data from the mammalian cortex to evaluate how the spike sorting performance of a close-packed extracellular multielectrode array is affected by bursting, which alters the shape and amplitude of spikes in a train. We also introduce an algorithmic framework to help evaluate how the number of electrodes in a multielectrode array affects spike sorting, examining how adding more electrodes yields data that can be spike sorted more easily. Our automated methodology may thus help with the evaluation of new electrode designs and configurations, providing empirical guidance on the kinds of electrodes that will be optimal for different brain regions, cell types, and species, for improving the accuracy of spike sorting. NEW & NOTEWORTHY We present an automated strategy for evaluating the spike recording performance of an extracellular multielectrode array, by enabling simultaneous recording of a neuron with both such an array and with patch clamp. We use our robot and accompanying algorithms to evaluate the performance of multielectrode arrays on supporting spike sorting.

Automated in vivo patch-clamp evaluation of extracellular multielectrode array spike recording capability.

Over the last few decades, a plethora of tools has been developed for neuroscientists to interface with the brain. Implementing these tools requires precisely removing sections of the skull to access the brain. These delicate cranial microsurgical procedures need to be performed on the sub-millimeter thick bone without damaging the underlying tissue and therefore, require significant training. Automating some of these procedures would not only enable more precise microsurgical operations, but also facilitate widespread use of advanced neurotechnologies. Here, we introduce the "Craniobot", a cranial microsurgery platform that combines automated skull surface profiling with a computer numerical controlled (CNC) milling machine to perform a variety of cranial microsurgical procedures on mice. The Craniobot utilizes a low-force contact sensor to profile the skull surface and uses this information to perform precise milling operations within minutes. We have used the Craniobot to perform intact skull thinning and open small to large craniotomies over the dorsal cortex.

Craniobot: A computer numerical controlled robot for cranial microsurgeries.

Neural computations occurring simultaneously in multiple cerebral cortical regions are critical for mediating behaviors. Progress has been made in understanding how neural activity in specific cortical regions contributes to behavior. However, there is a lack of tools that allow simultaneous monitoring and perturbing neural activity from multiple cortical regions. We engineered 'See-Shells'-digitally designed, morphologically realistic, transparent polymer skulls that allow long-term (>300 days) optical access to 45 mm of the dorsal cerebral cortex in the mouse. We demonstrate the ability to perform mesoscopic imaging, as well as cellular and subcellular resolution two-photon imaging of neural structures up to 600 µm deep. See-Shells allow calcium imaging from multiple, non-contiguous regions across the cortex. Perforated See-Shells enable introducing penetrating neural probes to perturb or record neural activity simultaneously with whole cortex imaging. See-Shells are constructed using common desktop fabrication tools, providing a powerful tool for investigating brain structure and function.

Cortex-wide neural interfacing via transparent polymer skulls.

Patch clamping is the gold standard measurement technique for cell-type characterization in vivo, but it has low throughput, is difficult to scale, and requires highly skilled operation. We developed an autonomous robot that can acquire multiple consecutive patch-clamp recordings in vivo. In practice, 40 pipettes loaded into a carousel are sequentially filled and inserted into the brain, localized to a cell, used for patch clamping, and disposed. Automated visual stimulation and electrophysiology software enables functional cell-type classification of whole cell-patched cells, as we show for 37 cells in the anesthetized mouse in visual cortex (V1) layer 5. We achieved 9% yield, with 5.3 min per attempt over hundreds of trials. The highly variable and low-yield nature of in vivo patch-clamp recordings will benefit from such a standardized, automated, quantitative approach, allowing development of optimal algorithms and enabling scaling required for large-scale studies and integration with complementary techniques.  In vivo patch-clamp is the gold standard for intracellular recordings, but it is a very manual and highly skilled technique. The robot in this work demonstrates the most automated in vivo patch-clamp experiment to date, by enabling production of multiple, serial intracellular recordings without human intervention. The robot automates pipette filling, wire threading, pipette positioning, neuron hunting, break-in, delivering sensory stimulus, and recording quality control, enabling in vivo cell-type characterization.

Autonomous patch-clamp robot for functional characterization of neurons in vivo: development and application to mouse visual cortex.

Microinjection into single cells in brain tissue is a powerful technique to study and manipulate neural stem cells. However, such microinjection requires expertise and is a low-throughput process. We developed the "Autoinjector", a robot that utilizes images from a microscope to guide a microinjection needle into tissue to deliver femtoliter volumes of liquids into single cells. The Autoinjector enables microinjection of hundreds of cells within a single organotypic slice, resulting in an overall yield that is an order of magnitude greater than manual microinjection. The Autoinjector successfully targets both apical progenitors (APs) and newborn neurons in the embryonic mouse and human fetal telencephalon. We used the Autoinjector to systematically study gap-junctional communication between neural progenitors in the embryonic mouse telencephalon and found that apical contact is a characteristic feature of the cells that are part of a gap junction-coupled cluster. The throughput and versatility of the Autoinjector will render microinjection an accessible high-performance single-cell manipulation technique and will provide a powerful new platform for performing single-cell analyses in tissue for bioengineering and biophysics applications.

Robotic platform for microinjection into single cells in brain tissue.

Cranial microsurgery is an essential procedure for accessing the brain through the skull that can be used to introduce neural probes that measure and manipulate neural activity. Neuroscientists have typically used tools such as high-speed drills adapted from dentistry to perform these procedures. As the number of technologies available for neuroscientists has increased, the corresponding cranial microsurgery procedures to deploy them have become more complex. Using a robotic tool that automatically performs these procedures could standardize cranial microsurgeries across neuroscience laboratories and democratize the more challenging procedures. We have recently engineered a robotic surgery platform that utilizes principles of computer numerical control (CNC) machining to perform a wide variety of automated cranial procedures. Here, we describe how to adapt, configure and use an inexpensive desktop CNC mill equipped with a custom-built surface profiler for performing CNC-guided microsurgery on mice. Detailed instructions are provided to utilize this 'Craniobot' for performing circular craniotomies for coverslip implantation, large craniotomies for implanting transparent polymer skulls for cortex-wide imaging access and skull thinning for intact skull imaging. The Craniobot can be set up in <2 weeks using parts that cost <$1,500, and we anticipate that the Craniobot could be easily adapted for use in other small animals.

Suhasa B. Kodandaramaiah

Department of Biomedical Engineering,
Department of Mechanical Engineering,
Graduate Program in Neuroscience

University of Minnesota

Manipulation of Single Neural Stem Cells and Neurons in Brain Slices using Robotic Microinjection

Suhasa B. Kodandaramaiah

.css-o250i3{font-size:18px;font-family:Open Sans,sans-serif;line-height:21.6px;}Department of Biomedical Engineering,Department of Mechanical Engineering,Graduate Program in Neuroscience

University of Minnesota

Manipulation of Single Neural Stem Cells and Neurons in Brain Slices using Robotic Microinjection

Department of Biomedical Engineering,
Department of Mechanical Engineering,
Graduate Program in Neuroscience