A connectome is not enough – what is still needed to understand the brain of<i>Drosophila</i>?

Scheffer, Louis K; Meinertzhagen, Ian A.

doi:10.1242/jeb.242740

Cited by 16 publications

(24 citation statements)

References 85 publications

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“…To further provide evidence that square grids are not from a random expectation, there was a search of functionality for the above six fruit fly brain regions (Figure 4). However, the functions of these regions are mostly unknown [23], and moreover, the local scale of the square grids would require an even finer scale of understanding of the animal neural system.…”

Section: Discussionmentioning

confidence: 99%

Detecting Square Grid Structure in an Animal Neuronal Network

Friedman

2022

NeuroSci

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An animal neural system ranges from a cluster of a few neurons to a brain of billions. At the lower range, it is possible to test each neuron for its role across a set of environmental conditions. However, the higher range requires another approach. One method is to disentangle the organization of the neuronal network. In the case of the entorhinal cortex in a rodent, a set of neuronal cells involved in spatial location activate in a regular grid-like arrangement. Therefore, it is of interest to develop methods to find these kinds of patterns in a neural network. For this study, a square grid arrangement of neurons is quantified by network metrics and then applied for identification of square grid structure in areas of the fruit fly brain. The results show several regions with contiguous clusters of square grid arrangements in the neural network, supportive of specialization in the information processing of the system.

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Section: Discussionmentioning

confidence: 99%

Detecting Square Grid Structure in an Animal Neuronal Network

Friedman

2022

NeuroSci

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“…Numerous studies have previously focused on the functional dissection of regional neural circuitry in the Drosophila , including that of vision [39, 40], olfaction [35], mushroom body [41], and central complex [29], to name a few. With advancements in data acquisition and processing, recent large-scale projects [23, 42] have been successful in generating detailed connectomes of the brain-wide neural circuitry, that go well beyond a single region. While a complete brain-wide wiring diagram is a necessary prerequisite, unraveling the underlying mechanistic pathways to interpolate function and behavior, is a problem that cannot be solved by gathering more data alone [23].…”

Section: Discussionmentioning

confidence: 99%

“…The vertex degree is the number of incoming and outgoing synapses of a neuron in the connectome (Table 1). 1: Comparing the EM-derived Janelia hemibrain connectome [23] against our stochastically generated connectome using p conn = 0.15. Both connectomic datasets were appropriately resized so that they span the same neuropils in the Drosophila hemibrain.…”

Section: Parameter Choice and Model Stabilitymentioning

confidence: 99%

Circuit Analysis of the Drosophila Brain using Connectivity-based Neuronal Classification Reveals Organization of Key Communication Pathways

Mehta

Goldin

Ascoli

2022

Preprint

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We present a functionally relevant, quantitative characterization of the neural circuitry of Drosophila melanogaster at the mesoscopic level of neuron types as classified exclusively based on network connectivity. Starting from a large neuron-to-neuron brain-wide connectome of the fruit fly, we use stochastic block modeling and spectral graph clustering to group neurons together into a common 'cell class' if they connect to neurons of other classes according to the same probability distributions. Thus, nodes of the identified circuit represent cell classes, while the directed edges represent the connection probabilities between neurons in those respective classes. We then characterize the connectivity-based cell classes with standard neuronal biomarkers, including neurotransmitters, developmental birthtimes, morphological features, spatial embedding, and functional anatomy. Mutual information indicates that connectivity-based classification reveals aspects of neurons that are not adequately captured by traditional classification schemes. Next, using graph-theoretic and random walk analyses to identify neuron classes as hubs, sources, or destinations, we detect patterns of directional connectivity and information flow that potentially underpin specific functional interactions in the Drosophila brain. We uncover a core of highly interconnected dopaminergic cell classes functioning as the backbone information highway for multisensory integration. We also recognize glutamatergic-dominant connections between the motor and optic regions, possibly facilitating circadian rhythmic activity. Additional predicted pathways pertain to spatial orientation, fight-or-flight response, and olfactory learning. Mapping the developmental birthtimes of neurons also pinpoints the temporal change of the circuit blueprint over the fly lifespan, revealing distinct critical growth periods of individual pathways. Our analysis provides experimentally testable hypotheses critically deconstructing complex brain function from organized connectomic architecture. We present a functionally relevant, quantitative characterization of the neural circuitry of Drosophila melanogaster at the mesoscopic level of neuron types as classified exclusively based on network connectivity. Starting from a large neuron-to-neuron brain-wide connectome of the fruit fly, we use stochastic block modeling and spectral graph clustering to group neurons together into a common 'cell class' if they connect to neurons of other classes according to the same probability distributions. Thus, nodes of the identified circuit represent cell classes, while the directed edges represent the connection probabilities between neurons in those respective classes. We then characterize the connectivity-based cell classes with standard neuronal biomarkers, including neurotransmitters, developmental birthtimes, morphological features, spatial embedding, and functional anatomy. Mutual information indicates that connectivity-based classification reveals aspects of neurons that are not adequately captured by traditional classification schemes. Next, using graph-theoretic and random walk analyses to identify neuron classes as hubs, sources, or destinations, we detect patterns of directional connectivity and information flow that potentially underpin specific functional interactions in the Drosophila brain. We uncover a core of highly interconnected dopaminergic cell classes functioning as the backbone information highway for multisensory integration. We also recognize glutamatergic-dominant connections between the motor and optic regions, possibly facilitating circadian rhythmic activity. Additional predicted pathways pertain to spatial orientation, fight-or-flight response, and olfactory learning. Mapping the developmental birthtimes of neurons also pinpoints the temporal change of the circuit blueprint over the fly lifespan, revealing distinct critical growth periods of individual pathways. Our analysis provides experimentally testable hypotheses critically deconstructing complex brain function from organized connectomic architecture.

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“…C. elegans was the first animal with a completely sequenced genome, achieved in the year 1998, followed by Drosophila in 2000 [22,23]. Apart from their well-annotated genomes, their main advantage as lab animals is short generation time, easy screening for mutants, a versatile toolbox for cell-lineage tracing and genetic manipulation, availability of connectivity diagrams for the nervous system, and the presence of sets of identifiable neurons [24][25][26][27][28]. Essential arguments for using an invertebrate model system in toxicological studies, instead of a mammal [19,29], are evolutionary conserved molecular mechanisms for development and cellular functions.…”

Section: Introductionmentioning

confidence: 99%

Looking at Developmental Neurotoxicity Testing from the Perspective of an Invertebrate Embryo

Bicker¹

2022

IJMS

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Developmental neurotoxicity (DNT) of chemical compounds disrupts the formation of a normal brain. There is impressive progress in the development of alternative testing methods for DNT potential in chemicals, some of which also incorporate invertebrate animals. This review briefly touches upon studies on the genetically tractable model organisms of Caenorhabditis elegans and Drosophila melanogaster about the action of specific developmental neurotoxicants. The formation of a functional nervous system requires precisely timed axonal pathfinding to the correct cellular targets. To address this complex key event, our lab developed an alternative assay using a serum-free culture of intact locust embryos. The first neural pathways in the leg of embryonic locusts are established by a pair of afferent pioneer neurons which use guidance cues from membrane-bound and diffusible semaphorin proteins. In a systematic approach according to recommendations for alternative testing, the embryo assay quantifies defects in pioneer navigation after exposure to a panel of recognized test compounds for DNT. The outcome indicates a high predictability for test-compound classification. Since the pyramidal neurons of the mammalian cortex also use a semaphorin gradient for neurite guidance, the assay is based on evolutionary conserved cellular mechanisms, supporting its relevance for cortical development.

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A connectome is not enough – what is still needed to understand the brain ofDrosophila?

Cited by 16 publications

References 85 publications

Detecting Square Grid Structure in an Animal Neuronal Network

Detecting Square Grid Structure in an Animal Neuronal Network

Circuit Analysis of the Drosophila Brain using Connectivity-based Neuronal Classification Reveals Organization of Key Communication Pathways

Looking at Developmental Neurotoxicity Testing from the Perspective of an Invertebrate Embryo

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