The Developmental Rules of Neural Superposition in Drosophila

SummaryComplicated neuronal circuits can be genetically encoded, but the underlying developmental algorithms remain largely unknown. Here, we describe a developmental algorithm for the specification of synaptic partner cells through axonal sorting in the Drosophila visual map. Our approach combines intravital imaging of growth cone dynamics in developing brains of intact pupae and data-driven computational modeling. These analyses suggest that three simple rules are sufficient to generate the seemingly complex neural superposition wiring of the fly visual map without an elaborate molecular matchmaking code. Our computational model explains robust and precise wiring in a crowded brain region despite extensive growth cone overlaps and provides a framework for matching molecular mechanisms with the rules they execute. Finally, ordered geometric axon terminal arrangements that are not required for neural superposition are a side product of the developmental algorithm, thus elucidating neural circuit connectivity that remained unexplained based on adult structure and function alone.PaperCli

Regulation of branching dynamics by axon-intrinsic asymmetries in Tyrosine Kinase Receptor signaling

Axonal branching allows a neuron to connect to several targets, increasing neuronal circuit complexity. While axonal branching is well described, the mechanisms that control it remain largely unknown. We find that in the Drosophila CNS branches develop through a process of excessive growth followed by pruning. In vivo high-resolution live imaging of developing brains as well as loss and gain of function experiments show that activation of Epidermal Growth Factor Receptor (EGFR) is necessary for branch dynamics and the final branching pattern. Live imaging also reveals that intrinsic asymmetry in EGFR localization regulates the balance between dynamic and static filopodia. Elimination of signaling asymmetry by either loss or gain of EGFR function results in reduced dynamics leading to excessive branch formation. In summary, we propose that the dynamic process of axon branch development is mediated by differential local distribution of signaling receptors

Mutual inhibition among neighbouring neurons regulates axonal target choice and robustness of developing brain maps

During brain development, axons of neighbouring neurons navigate long distances in a complex and contradictory environment of guidance cues and morphogen signals to make differential connectivity decisions and generate functional brain circuits. Such maps display a high degree of accuracy and reproducibility across individuals, hinting at mechanisms that ensure robustness of neuronal wiring in the face of environmental and genetic variation. The identities and properties of these robustness mechanisms, whether they are genetically encoded and how they interact with axon guidance cues are unknown. Using quantitative anatomy, genetics and mathematical modelling approaches we provide evidence that mutual inhibition between neighbouring postmitotic neurons via Notch signalling imparts developmental plasticity and robustness upon developing neuronal circuits. First, we generate a quantitative anatomical description for a set of Drosophila melanogaster CNS visual system neurons. Next, we use genetic approaches to show that small subsets of neighbouring neurons communicate with each other during axonal outgrowth to generate alternative, high versus low, states of Notch activity. Furthermore, Notch activity levels attenuate a neuron's response to axon guidance signals, allowing neurons to make alternative and mutually exclusive axon target choices. Loss of Notch activity in a given neuron autonomously alters it's axon target choice. However, because neighbouring cells then adopt the alternative choice, the overall normal connectivity pattern is preserved. Mathematical modelling shows that mutual inhibition during axon outgrowth is a form of developmental plasticity that generates a very high degree of robustness in neuronal wiring.status: publishe

Earlier Diagnosis of Progressive Disease during Bevacizumab Treatment Using O-(2-18F-Fluorethyl)-L-tyrosine Positron Emission Tomography in Comparison with Magnetic Resonance Imaging.

AbstractAntiangiogenic treatment using bevacizumab in brain tumor patients may cause difficulties in the diagnosis of tumor progression (ie, nonenhancing tumor progression). Newly defined criteria for treatment assessment and diagnosis of tumor progression (ie, RANO [Response Assessment in Neuro-Oncology] criteria) have implemented signal alterations on T2/fluid-attenuated inversion recovery (FLAIR) sequences to changes in contrast enhancement. However, T2/FLAIR hyperintensity may be influenced by other causes (eg, radiation-induced leukoencephalopathy, peritumoral edema, gliosis). Positron emission tomography using the radiolabeled amino acid O-(2-[18F]fluoroethyl)-l-tyrosine (18F-FET-PET) may help detect the metabolically active tumor extent. We present 18F-FET-PET imaging findings in a glioblastoma patient during bevacizumab treatment suggesting an earlier diagnosis of tumor progression than magnetic resonance imaging changes, which are based on the RANO criteria

The Evolution and Development of Neural Superposition

Visual systems have a rich history as model systems for the discovery and understanding of basic principles underlying neuronal connectivity. The compound eyes of insects consist of up to thousands of small unit eyes that are connected by photoreceptor axons to set up a visual map in the brain. The photoreceptor axon terminals thereby represent neighboring points seen in the environment in neighboring synaptic units in the brain. Neural superposition is a special case of such a wiring principle, where photoreceptors from different unit eyes that receive the same input converge upon the same synaptic units in the brain. This wiring principle is remarkable, because each photoreceptor in a single unit eye receives different input and each individual axon, among thousands others in the brain, must be sorted together with those few axons that have the same input. Key aspects of neural superposition have been described as early as 1907. Since then neuroscientists, evolutionary and developmental biologists have been fascinated by how such a complicated wiring principle could evolve, how it is genetically encoded, and how it is developmentally realized. In this review article, we will discuss current ideas about the evolutionary origin and developmental program of neural superposition. Our goal is to identify in what way the special case of neural superposition can help us answer more general questions about the evolution and development of genetically "hard-wired" synaptic connectivity in the brain