59 research outputs found

    Calcium imaging analysis - how far have we come?

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    Techniques for calcium imaging were first demonstrated in the mid-1970s, whilst tools to analyse these markers of cellular activity are still being developed and improved today. For image analysis, custom tools were developed within labs and until relatively recently, software packages were not widely available between researchers. We will discuss some of the most popular methods for calcium imaging analysis that are now widely available and describe why these protocols are so effective. We will also describe some of the newest innovations in the field that are likely to benefit researchers, particularly as calcium imaging is often an inherently low signal-to-noise method. Although calcium imaging analysis has seen recent advances, particularly following the rise of machine learning, we will end by highlighting the outstanding requirements and questions that hinder further progress and pose the question of how far we have come in the past sixty years and what can be expected for future development in the field

    Identification of inhibitory premotor interneurons activated at a late phase in a motor cycle during Drosophila larval locomotion

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    This work was supported by a MEXT/JSPS KAKENHI Grant Numbers, 22115002 (to A.N.) and 221S0003 (to A.N. and Y.I.), and 15H04255 (to A.N.). The work was also supported by Janelia Research Campus (Howard Hughes Medical Institute).Rhythmic motor patterns underlying many types of locomotion are thought to be produced by central pattern generators (CPGs). Our knowledge of how CPG networks generate motor patterns in complex nervous systems remains incomplete, despite decades of work in a variety of model organisms. Substrate borne locomotion in Drosophila larvae is driven by waves of muscular contraction that propagate through multiple body segments. We use the motor circuitry underlying crawling in larval Drosophila as a model to try to understand how segmentally coordinated rhythmic motor patterns are generated. Whereas muscles, motoneurons and sensory neurons have been well investigated in this system, far less is known about the identities and function of interneurons. Our recent study identified a class of glutamatergic premotor interneurons, PMSIs (period-positive median segmental interneurons), that regulate the speed of locomotion. Here, we report on the identification of a distinct class of glutamatergic premotor interneurons called Glutamatergic Ventro-Lateral Interneurons (GVLIs). We used calcium imaging to search for interneurons that show rhythmic activity and identified GVLIs as interneurons showing wave-like activity during peristalsis. Paired GVLIs were present in each abdominal segment A1-A7 and locally extended an axon towards a dorsal neuropile region, where they formed GRASP-positive putative synaptic contacts with motoneurons. The interneurons expressed vesicular glutamate transporter (vGluT) and thus likely secrete glutamate, a neurotransmitter known to inhibit motoneurons. These anatomical results suggest that GVLIs are premotor interneurons that locally inhibit motoneurons in the same segment. Consistent with this, optogenetic activation of GVLIs with the red-shifted channelrhodopsin, CsChrimson ceased ongoing peristalsis in crawling larvae. Simultaneous calcium imaging of the activity of GVLIs and motoneurons showed that GVLIs' wave-like activity lagged behind that of motoneurons by several segments. Thus, GVLIs are activated when the front of a forward motor wave reaches the second or third anterior segment. We propose that GVLIs are part of the feedback inhibition system that terminates motor activity once the front of the motor wave proceeds to anterior segments.Publisher PDFPeer reviewe

    Identifying neural substrates of competitive interactions and sequence transitions during mechanosensory responses in Drosophila.

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    Nervous systems have the ability to select appropriate actions and action sequences in response to sensory cues. The circuit mechanisms by which nervous systems achieve choice, stability and transitions between behaviors are still incompletely understood. To identify neurons and brain areas involved in controlling these processes, we combined a large-scale neuronal inactivation screen with automated action detection in response to a mechanosensory cue in Drosophila larva. We analyzed behaviors from 2.9x105 larvae and identified 66 candidate lines for mechanosensory responses out of which 25 for competitive interactions between actions. We further characterize in detail the neurons in these lines and analyzed their connectivity using electron microscopy. We found the neurons in the mechanosensory network are located in different regions of the nervous system consistent with a distributed model of sensorimotor decision-making. These findings provide the basis for understanding how selection and transition between behaviors are controlled by the nervous system

    Dedicated photoreceptor pathways in Drosophila larvae mediate navigation by processing either spatial or temporal cues.

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    To integrate changing environmental cues with high spatial and temporal resolution is critical for animals to orient themselves. Drosophila larvae show an effective motor program to navigate away from light sources. How the larval visual circuit processes light stimuli to control navigational decision remains unknown. The larval visual system is composed of two sensory input channels, Rhodopsin5 (Rh5) and Rhodopsin6 (Rh6) expressing photoreceptors (PRs). We here characterize how spatial and temporal information are used to control navigation. Rh6-PRs are required to perceive temporal changes of light intensity during head casts, while Rh5-PRs are required to control behaviors that allow navigation in response to spatial cues. We characterize how distinct behaviors are modulated and identify parallel acting and converging features of the visual circuit. Functional features of the larval visual circuit highlight the principle of how early in a sensory circuit distinct behaviors may be computed by partly overlapping sensory pathways

    Organization of the Drosophila larval visual circuit

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    Visual systems transduce, process and transmit light-dependent environmental cues. Computation of visual features depends on the types of photoreceptor neurons (PR) present, the organization of the eye and the wiring of the underlying neural circuit. Here, we describe the circuit architecture of the visual system of Drosophila larvae by mapping the synaptic wiring diagram and neurotransmitters. By contacting different targets, the two larval PR-subtypes create parallel circuits potentially underlying the computation of absolute light intensity and temporal light changes already within this first visual processing center. Locally processed visual information then signals via dedicated projection interneurons to higher brain areas including the lateral horn and mushroom body. The stratified structure of the LON suggests common organizational principles with the adult fly and vertebrate visual systems. The complete synaptic wiring diagram of the LON paves the way to understanding how circuits with reduced numerical complexity control wide ranges of behaviors

    Four individually identified paired dopamine neurons signal reward in larval Drosophila

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    Dopaminergic neurons serve multiple functions, including reinforcement processing during associative learning [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11 and 12]. It is thus warranted to understand which dopaminergic neurons mediate which function. We study larval Drosophila, in which only approximately 120 of a total of 10,000 neurons are dopaminergic, as judged by the expression of tyrosine hydroxylase (TH), the rate- limiting enzyme of dopamine biosynthesis [ 5 and 13]. Dopaminergic neurons mediating reinforcement in insect olfactory learning target the mushroom bodies, a higher-order “cortical” brain region [ 1, 2, 3, 4, 5, 11, 12, 14 and 15]. We discover four previously undescribed paired neurons, the primary protocerebral anterior medial (pPAM) neurons. These neurons are TH positive and subdivide the medial lobe of the mushroom body into four distinct subunits. These pPAM neurons are acutely necessary for odor-sugar reward learning and require intact TH function in this process. However, they are dispensable for aversive learning and innate behavior toward the odors and sugars employed. Optogenetical activation of pPAM neurons is sufficient as a reward. Thus, the pPAM neurons convey a likely dopaminergic reward signal. In contrast, DL1 cluster neurons convey a corresponding punishment signal [5], suggesting a cellular division of labor to convey dopaminergic reward and punishment signals. On the level of individually identified neurons, this uncovers an organizational principle shared with adult Drosophila and mammals [ 1, 2, 3, 4, 7, 9 and 10] (but see [6]). The numerical simplicity and connectomic tractability of the larval nervous system [ 16, 17, 18 and 19] now offers a prospect for studying circuit principles of dopamine function at unprecedented resolution
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