Event Abstract

In vivo multi-single-unit extracellular recordings from identified neural populations in fruit flies

  • 1 Cambridge University, United Kingdom
  • 2 HHMI, Janelia Farm Research Campus, United States

The fruit fly’s genetic toolbox makes it a promising model system for systems neuroscience. Neural recordings from its brain have so far been made using single-channel glass electrodes or fluorescence imaging with genetically encoded calcium indicators. The former has high temporal resolution but is limited to single neurons; the latter can capture multi-neuron activity with high spatial resolution, but has poor temporal resolution. Multi-unit recordings with high temporal specificity can be achieved with multi-electrode probes, but existing probes are an order of magnitude too large for the fruit fly brain. Here, we describe the development of a new set of miniature multi-electrode probes with pad sizes that are significantly smaller than currently available probes, and yet of low enough impedance to capture spiking activity in the fruit fly brain with single neuron resolution. Using a focused ion beam system to both cut through and deposit platinum on commercially available multi-electrode probes from NeuroNexus, we designed probes which are ~20 microns wide, and contain up to five shanks. Each shank terminates in a recording pad with a surface area of roughly 25 square microns. With four- or five-channel probes we could spike-sort up to five independent units from central brain recordings. Simultaneous loose patch recordings from identified neurons confirmed that the waveforms detected belonged to single units. The power of Drosophila is in its well-developed genetics, with the free availability of thousands of fly lines that allow the targeted expression of exogenous proteins to selected neural sub-populations. Genetic targeting in this manner allows responses in an entire brain region, such as the central complex (CC), to potentially be mapped cell-type by cell-type in small groups of a few neurons each. We used the Gal4-UAS system to express channelrhodopsin-2 (ChR2) in small populations of identified neurons in sub-regions of the CC. Loose-patch recordings confirmed that a brief pulse of blue light elicited one or more spikes in ChR2-expressing neurons with a latency low enough to discriminate directly activated neurons from those activated through monosynaptic connections with ChR2-positive neurons. In a manner similar to that employed in a recent paper where the authors used viruses to target ChR2 to specific neurons in the rodent auditory cortex [2], we could then identify a subset of the spike-sorted units as belonging to the genetically specified neural population based on their responses to blue light. We are now using this approach to target probes to areas that maximize our yield of identified neurons. Our miniaturized multi-site probes allow us to record from small and densely packed neurons. We have used these probes to make the first multi-single-unit extracellular recordings in the fruit fly, but probes with similar site sizes and spacing may also be useful for recordings in packed areas of the vertebrate brain. Finally, this technique can be combined with genetically targeted expression of ChR2 to perform in vivo recordings of multiple identified neurons in the fruit fly central brain.

References

1. Lima, Znamenskiy, Hromadka, and Zador (PLoS ONE, 2009)

Conference: Computational and Systems Neuroscience 2010, Salt Lake City, UT, United States, 25 Feb - 2 Mar, 2010.

Presentation Type: Poster Presentation

Topic: Poster session III

Citation: Ahrens MB, Barbic M, Barbarits B, Jamieson BG and Jayaraman V (2010). In vivo multi-single-unit extracellular recordings from identified neural populations in fruit flies. Front. Neurosci. Conference Abstract: Computational and Systems Neuroscience 2010. doi: 10.3389/conf.fnins.2010.03.00189

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Received: 03 Mar 2010; Published Online: 03 Mar 2010.

* Correspondence: Vivek Jayaraman, HHMI, Janelia Farm Research Campus, Ashburn, United States, vivek@janelia.hhmi.org