Fly seizure EEG: field potential activity in the Drosophila brain

Abstract

Hypersynchronous neural activity is a characteristic feature of seizures. Although many Drosophila mutants of epilepsy-related genes display clear behavioral spasms and motor unit hyperexcitability, field potential measurements of aberrant hypersynchronous activity across brain regions during seizures have yet to be described. Here, we report a straightforward method to observe local field potentials (LFPs) from the Drosophila brain to monitor ensemble neural activity during seizures in behaving tethered flies. High frequency stimulation across the brain reliably triggers a stereotypic sequence of electroconvulsive seizure (ECS) spike discharges readily detectable in the dorsal longitudinal muscle (DLM) and coupled with behavioral spasms. During seizure episodes, the LFP signal displayed characteristic large-amplitude oscillations with a stereotypic temporal correlation to DLM flight muscle spiking. ECS-related LFP events were clearly distinct from rest- and flight-associated LFP patterns. We further characterized the LFP activity during different types of seizures originating from genetic and pharmacological manipulations. In the ‘bang-sensitive’ sodium channel mutant bangsenseless (bss), the LFP pattern was prolonged, and the temporal correlation between LFP oscillations and DLM discharges was altered. Following administration of the pro-convulsant GABA_A blocker picrotoxin, we uncovered a qualitatively different LFP activity pattern, which consisted of a slow (1-Hz), repetitive, waveform, closely coupled with DLM bursting and behavioral spasms. Our approach to record brain LFPs presents an initial framework for electrophysiological analysis of the complex brain-wide activity patterns in the large collection of Drosophila excitability mutants.

Keywords:

• Electroencephalogram
• local field potential
• synchronization
• epilepsy
• electro-convulsion
• flight
• dorsal longitudinal muscle

Acknowledgements

We dedicate this article in commemoration of Prof. Marla Sokolowski's unique contributions to the development of behavioral genetics. We also acknowledge the long-running and spirited collaboration between the Sokolowski and Wu labs. We thank Prof. Toshi Kitamoto, and members of the Wu Lab, particularly Tristan O'Harrow and Atsushi Ueda, for their helpful discussions over the course of this project.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This work was supported by NIH grants [NS111122, AG051513] to CFW, and an Iowa Neuroscience Institute fellowship to AI.