Periodic Reporting for period 1 - DECISIONSEQ (Neural bases of behavioral choices and sequences)
Reporting period: 2018-11-26 to 2020-11-25
Many behaviors are physically mutually exclusive and therefore cannot occur simultaneously. Competitive interactions must exist that ensure that when one behavior is selected, other, competing behaviors are being suppressed. The outcome of these competitive interactions can be influenced by different factors and offen animals make different behavioral choices depending on the situation or their internal state. This allows the animal to do right thing given the circumstances, which is essential to ensure survival across species. Indeed the capacity to choose appropriate behaviours is impaired in many neuropsychiatric disorders. However, the neural circuit mechanisms that ensure this flexible selection of behaviors are not known with cellular and synaptic resolution. This is due to the difficulty in establishing causal relationships between single neurons and behaviors and mapping synaptic connectivity across the nervous system in big and complex brains with many neurons and many connections. To overcome these difficulties, we take advantage of Drosophila larva to address these questions. It has a compact brain which allowed the volume of electron microscopy (EM) images of the entire nervous system to be acquired and neuronal circuits can be mapped with synaptic resolution across the nervous system. In addition, the powerful genetic tools and rapid reproductive cycle make it possible to manipulate neuronal activity in a cell-type specific manner and quickly detect the resulting behavioral changes and thus establish the causal link between neurons and their behavior function. Drawing on the power of these methods which allowsto identify entry points into the circuits and then reconstruct their connections we investigated the neural basis of competitive interactions between behaviors that larvae perform in response to an external stimulus. This work set the basis for further investigations of the detailed neural circuits mechanisms of competitive interactions and their modulations by contextual and internal state information at the level of molecules, neural networks and behavior by the researcher at her next postion as a team leader and as preliminary work to secure funding for these investigations.
Using high-speed video tracking combined with a machine learning algorithms that allow to automatically classify larval behavior genetic manipulation of sparse neuronal populations and single neurons and neuroanatomy and synaptic connectivity studies, we map the neural circuit elements and pathways underlying the five different actions that occur in response to a mechanical stimulus, the air-puff. In response to an air-puff, larvae perform five different type of escape or avoidance actions: Hunch, Bend, Stop, Back-up and Crawl. By quantifying changes in behavioral probability in the different actions upon neuronal silencing, we identify neuronal elements that could underlie the competitive interaction between the five behaviors. Using neuroanatomy studies, we determine the identity of neurons involved in mechanosensory responses (Masson et al., Plos genetics, 2020) and found neurons that are located downstream of two types of sensory neurons (chordotonal and multidendritic class III neurons) that we previously found were involved in sensing air-puff or their first order partners. Our data revealed new putative second order interneurons and ascending pathways in the mechanosensory network as well as a feedback from the premotor domain. Overall, our findings suggest that the selection of behaviors occurs not in specialized centers but rather through a distributed process involving different regions of the nervous system. Furthermore, in order to investigate the functional contributions of individual circuit elements, we identify the neurotransmitter identity of key neurons (to determine whether they are excitatory and inhibitory. This combined with tracing on connectivity in electron microscopy and functional studies will reveal circuits motifs involved in competitive interactions between actions. In addition, the five behaviors are often organized in a sequence where the individual actions need to be ordered one after the other. We thus further develop a framework for using our dataset for studying the neural basis of sequence transitions during larval response to an air-puff and identify circuit elements involved in sequence generation. In addition to a peer-reviewed publication (Masson et al, 2020), results from this were also presented at an International conference and will be used to prepare two additional manuscripts.
Understanding the neural circuit mechanisms underlying competitive interactions and sequence transitions in Drosophila larva a model organism that is amenable for neural circuit analysis will advance the understanding of theses processes in general by providing inspiration for new models and hypotheses that can be tested in other organisms including humans. Canonical circuit motifs are known to be shared across phyla so identifying circuit mechanisms underlying the selection and transition between behaviors will contribute to the understanding of the basic principles of neural circuit implementation of these processes in general, in both health and disease. The similarities at the molecular level (an estimate of 60% of genes are conserved between flies and humans) further suggest that insights gained in the Drosophila brain might also contribute to our understanding of neural mechanisms in other organisms including ourselves.