Patch-walking electrophysiology recordings
Data files
Feb 18, 2025 version files 273.33 MB
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Patch-walk_recordings_run1.zip
273.33 MB
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README.md
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Abstract
Significant technical challenges exist when measuring synaptic connections between neurons in living brain tissue. The patch clamping technique, when used to probe for synaptic connections, is manually laborious and time-consuming. To improve its efficiency, we pursued another approach: instead of retracting all patch clamping electrodes after each recording attempt, we cleaned just one of them and reused it to obtain another recording while maintaining the others. With one new patch clamp recording attempt, many new connections can be probed. By placing one pipette in front of the others in this way, one can “walk” across the mouse brain slice, termed “patch-walking.” We performed 136 patch clamp attempts for two pipettes, achieving 71 successful whole cell recordings (52.2%). Of these, we probed 29 pairs (i.e., 58 bidirectional probed connections) averaging 91 μm intersomatic distance, finding 3 connections. Patch-walking yields 80-92% more probed connections, for experiments with 10-100 cells than the traditional synaptic connection searching method.
https://doi.org/10.5061/dryad.x69p8cztq
Description of the data and file structure
Source data needed to recreate the primary results shown in Figures and electrophysiological recordings. Zip file includes electrophysiology recordings in .abf files where all neurons patched were tested with current clamp (IC) protocols to study synaptic connectivity.
42 .abf files are included in the zip that represent the connectivity matrix described in Figure 3 described in the Patch-walking paper. Naming convention is "23512###" with the ### representing each current clamp protocol run. Each pre-synaptic neuron was probed with 3 traces while reading the electrical output of the post-synaptic neuron and vice versa. The .abf files can be viewed in the pClamp Software Suite provided by Molecular Devices or alternatively can be viewed and analyzed in Python using the pyABF library.
Data is structured by date and the numeral of each file is a new sweep of IC protocol. Data collected from the patcherBot for patch-walking was based on code through autopatcher.org. Alternatively, for semi-automated patch clamping, users may use pipette cleaning as a method for reuse of pipettes (https://github.com/mightenyip/Pipette-Cleaning-Software). Current clamp and voltage clamp protocols were established as described by the Allen Institute for Brain Science.