title: Closed-Loop Behavioral Control Increases Coherence in the Fly Brain.
abstract: A crucial function of the brain is to be able to distinguish whether or not changes in the environment are caused by one's own actions. Even the smallest brains appear to be capable of making this distinction, as has been shown by closed-loop behavioral experiments in flies controlling visual stimuli in virtual reality paradigms. We questioned whether activity in the fruit fly brain is different during such closed-loop behavior, compared with passive viewing of a stimulus. To address this question, we used a procedure to record local field potential (LFP) activity across the fly brain while flies were controlling a virtual object through their movement on an air-supported ball. The virtual object was flickered at a precise frequency (7 Hz), creating a frequency tag that allowed us to track brain responses to the object while animals were behaving. Following experiments under closed-loop control, we replayed the same stimulus to the fly in open loop, such that it could no longer control the stimulus. We found identical receptive fields and similar strength of frequency tags across the brain for the virtual object under closed loop and replay. However, when comparing central versus peripheral brain regions, we found that brain responses were differentially modulated depending on whether flies were in control or not. Additionally, coherence of LFP activity in the brain increased when flies were in control, compared with replay, even if motor behavior was similar. This suggests that processes associated with closed-loop control promote temporal coordination in the insect brain.
  
  
  CONCLUSIONS
  We show that closed-loop control of a visual stimulus promotes temporal coordination across the Drosophila brain, compared with open-loop replay of the same visual sequences. This is significant because it suggests that, to understand goal-directed behavior or visual attention in flies, it may be most informative to sample neural activity from multiple regions across the brain simultaneously, and to examine temporal relationships (e.g., coherence) between these regions.
authors.affiliation: Queensland Brain Institute, The University of Queensland, Brisbane, Australia 4072.
authors.forename: Angelique C
authors.initials: AC
authors.lastname: Paulk
authors.affiliation: Queensland Brain Institute, The University of Queensland, Brisbane, Australia 4072.
authors.forename: Leonie
authors.initials: L
authors.lastname: Kirszenblat
authors.affiliation: Queensland Brain Institute, The University of Queensland, Brisbane, Australia 4072.
authors.forename: Yanqiong
authors.initials: Y
authors.lastname: Zhou
authors.affiliation: Queensland Brain Institute, The University of Queensland, Brisbane, Australia 4072 b.vanswinderen@uq.edu.au.
authors.forename: Bruno
authors.initials: B
authors.lastname: van Swinderen
mesh_terms: D000704:Analysis of Variance; D000818:Animals; D001522:Behavior, Animal / Q000502:physiology*; D001921:Brain / Q000502:physiology*; D001931:Brain Mapping; D004331:Drosophila melanogaster; D005074:Evoked Potentials, Visual / Q000502:physiology; D005260:Female; D008124:Locomotion; D010775:Photic Stimulation; D014794:Visual Fields / Q000502:physiology*; D014796:Visual Perception / Q000502:physiology*
keywords: Drosophila; SSVEP; behavior; closed-loop; electrophysiology; vision