Understanding the functional principles of the mammalian cortical circuit is a major challenge in neuroscience. To make progress towards this understanding, one needs to be able to assess the behavioural dynamics of individual neuronal elements of this circuit. Manual whole-cell recording (WCR) in vivo is recognised as the “gold standard” method for electrophysiological interrogation of individual neurons. It allows subthreshold and suprathreshold signals to be recorded, perturbations to be applied through current injection, and DNA vectors to be directly delivered into the patched cells as part of the pipette internal solution. Unfortunately, the WCR technique for in vivo application is a “blind” procedure and has a low-throughput. In addition, the genetic and morphological identity of the recorded neuron often cannot be accounted for. The inherent cell-type non selectivity of this technique can be overcome by combining WCR with two-photon laser scanning microscopy, and targeting recordings to specifically labelled individual cells or cell classes. Targeted electrophysiological interrogation allows one to examine the properties of both single cells and neuronal assemblies and, additionally, the role of cell type-specific proteins in orchestrating neuronal responses. Targeted recordings in vivo may enable to test a wide range of hypotheses related to information processing in the cortical circuits. However, probing and studying the properties of individual cells in live animal preparations remains a challenge in neuroscience. In particular, precise vision-guided control of patch pipette motion and viewpoint generation of microscope objective for targeted single-cell electrophysiological interrogation is problematic. It requires specialised skills acquired through extensive practice and training by individual operators. Although automatic patch clamp technology has been in use for some years exclusively for cell culture-based paradigms, only recently has Kodandaramaiah et al. demonstrated a “blind” automated patch clamp system for in vivo recordings. However, a fully automatic method for in vivo WCR targeting specific cells or cell-types has not been implemented in any robotic system so far. In this study an automated two-photon targeted whole-cell patch clamping algorithm is demonstrated as a workable solution. The aim of this work was to develop a robotic integrated targeted autopatcher that minimised labour intensive procedures and increased the throughput both in blind and two-photon targeted WCR in live animals. The system automatically controls a micromanipulator, a microelectrode signal amplifier a two-photon microscope and a custom made regulator for controlling the internal pressure of the pipette. The two-photon microscope acquires images of fluorescently labelled cells, and cell-targets for patch clamp are selected via a point-and-click graphical user interface. Optical coordinates are initially converted to the micromanipulator coordinate system and a suitable path calculated to guide the patch pipette towards the target. This platform allows to compensate for brain tissue deformation and subsequent neuronal target movement caused by pipette insertion. As proof-of-concept, the system was tested in both “blind” and two-photon targeted paradigms and achieved performances comparable to human operators, in terms of yield, recording quality and operational speed. Hit rate for “blind” WCR was 51.4% (n=18, 35 attempts across 5 mice). RITA was also calibrated and tested for targeting specific cell types in the cortex of intact mouse brain labelled via fluorescent dye loading (e.g. Oregon Green BAPTA-1 and/or Sulforhodamine 101). Pipettes were automatically guided to the target cells and recordings obtained from visually identified neurons as well as astrocytes. These results prove the feasibility of robotic targeted WCR patch clamp in vivo and establish this system as a powerful tool for automated electrophysiological experiments in the brain.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:733127 |
| Date | January 2016 |
| Creators | Annecchino, Luca |
| Contributors | Schultz, Simon |
| Publisher | Imperial College London |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | http://hdl.handle.net/10044/1/56991 |
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