Periodic Reporting for period 1 - BICE (Circuit mechanisms for behavioral choice from complete CNS activity and connectivity maps)
Reporting period: 2019-09-02 to 2021-09-01
Studying neuronal mechanisms of entire neuronal circuits with single cell resolution requires a comprehensive understanding of neuronal activity, synaptic connectivity and neurotransmitter identity for each individual neuron. The project was aimed to develop a method to overcome this challenge. The approach was applied to study the neuronal mechanism of action selection in the larva of Drosophila melanogaster.
Two main problems were address: 1) Developing the required steps to combine functional and structural datasets. 2) Identifying behavior and behavioral transition specific neuronal circuit elements and their implementation in the connectome.
The methodology can be applied in small model organisms and the techniques and developed tools can be adapted individually to other model organism and research question. Therefore, it is a broad platform for other neuroscientists to develop circuit related research questions on the foundation of connectomics.
The objectives address the individual challenges of the project: a) acquisition and analysis of multiple whole nervous system functional imaging datasets with single cell resolution, b) acquisition of multiple electron microscopy data sets to gain cell identity from different samples and data set modalities and c) circuit specific genetic manipulation to access the role of single neurons in the circuit dynamic.
The researcher successfully implemented the methodology. Its was applied studying the circuit mechanism of action selection in the fly larva. Specific brain regions and neurons for state-dependency, and promoting and maintaining actions were identified.
Two main problems were address: 1) Developing the required steps to combine functional and structural datasets. 2) Identifying behavior and behavioral transition specific neuronal circuit elements and their implementation in the connectome.
The methodology can be applied in small model organisms and the techniques and developed tools can be adapted individually to other model organism and research question. Therefore, it is a broad platform for other neuroscientists to develop circuit related research questions on the foundation of connectomics.
The objectives address the individual challenges of the project: a) acquisition and analysis of multiple whole nervous system functional imaging datasets with single cell resolution, b) acquisition of multiple electron microscopy data sets to gain cell identity from different samples and data set modalities and c) circuit specific genetic manipulation to access the role of single neurons in the circuit dynamic.
The researcher successfully implemented the methodology. Its was applied studying the circuit mechanism of action selection in the fly larva. Specific brain regions and neurons for state-dependency, and promoting and maintaining actions were identified.
Scientific project - Identification of neuronal circuit mechanisms during action selection on single-cell level
To achieve to goal of the project, the researcher performed whole brain functional imaging experiment, while monitoring the behaviors. Next, neurons, whose activity were correlated or anti-correlated with a behavior transition were identified in the functional connectivity maps. In order to locate the neurons in the connectome, the researcher acquired an electron microscopy volume from the light microscopy volume. To achieve that goal, the fixation protocol for FIB SEM (focus ion beam scanning electron microscopy) imaging was optimized to increase contrast with minimal tissue damage. Afterwards, both volumes, electron and light microscopy volume, were registered with single cell accuracy to guarantee the unambiguous location of the cells in the connectome. Subsequently the neuronal backbone were reconstructed until identification. The researcher generated the necessary data and identified some neurons between the different modalities. The function of the neurons in the neuronal circuit were tested by performing optogenetic activation experiments of the identified neurons and their postsynaptic partners. Notably, the researcher could show that a neuron might evoke a certain action by inhibiting competing behaviors via different descending neurons.
Ultimately, the researcher identify brain regions and single cells which play a significant role in behavior reporting, state-dependency and generating efferent copies. Adapting the same workflow, the researcher also generated whole brain neurotransmitter expression maps and identified neurotransmitter positive cells in the connectome. This enables the researcher to identify inhibitory and excitatory neurons and refine our models of how single neurons and complete neuronal circuits evoke and maintain new actions.
Exploitation, dissemination and communication
The researcher participated in the following workshops: a) Leadership and Management course, Supervision for undergraduate students and Grant writing.
Results of the project were communicated at the FENS conference (poster), Modulation of Neural Circuits and Behavior conference (poster) and presented during two department seminars, the postdoc seminar series (MPI for Brain Research), TechEM seminar series (international, online) and Monthly Maggot Monday seminar series (international, online).
To achieve to goal of the project, the researcher performed whole brain functional imaging experiment, while monitoring the behaviors. Next, neurons, whose activity were correlated or anti-correlated with a behavior transition were identified in the functional connectivity maps. In order to locate the neurons in the connectome, the researcher acquired an electron microscopy volume from the light microscopy volume. To achieve that goal, the fixation protocol for FIB SEM (focus ion beam scanning electron microscopy) imaging was optimized to increase contrast with minimal tissue damage. Afterwards, both volumes, electron and light microscopy volume, were registered with single cell accuracy to guarantee the unambiguous location of the cells in the connectome. Subsequently the neuronal backbone were reconstructed until identification. The researcher generated the necessary data and identified some neurons between the different modalities. The function of the neurons in the neuronal circuit were tested by performing optogenetic activation experiments of the identified neurons and their postsynaptic partners. Notably, the researcher could show that a neuron might evoke a certain action by inhibiting competing behaviors via different descending neurons.
Ultimately, the researcher identify brain regions and single cells which play a significant role in behavior reporting, state-dependency and generating efferent copies. Adapting the same workflow, the researcher also generated whole brain neurotransmitter expression maps and identified neurotransmitter positive cells in the connectome. This enables the researcher to identify inhibitory and excitatory neurons and refine our models of how single neurons and complete neuronal circuits evoke and maintain new actions.
Exploitation, dissemination and communication
The researcher participated in the following workshops: a) Leadership and Management course, Supervision for undergraduate students and Grant writing.
Results of the project were communicated at the FENS conference (poster), Modulation of Neural Circuits and Behavior conference (poster) and presented during two department seminars, the postdoc seminar series (MPI for Brain Research), TechEM seminar series (international, online) and Monthly Maggot Monday seminar series (international, online).
The MSCA enabled the development of techniques, which will change the approach of addressing neuronal circuit questions. The developed tools can be adapted to different model organisms and will drive the comparative analysis of nervous systems.
Beyond the state of the art achievements are: Close-loop whole brain functional imaging, registration of brain tissue from different data modalities, and bridging the gap between neuron identity and large neuronal dynamic data sets. The outcome of the project will affect the neuroscience community and enables a deeper understanding of neuronal circuit questions.
Beyond the state of the art achievements are: Close-loop whole brain functional imaging, registration of brain tissue from different data modalities, and bridging the gap between neuron identity and large neuronal dynamic data sets. The outcome of the project will affect the neuroscience community and enables a deeper understanding of neuronal circuit questions.