A connectome is not enough - what is still needed to understand the brain of Drosophila?

A leaky integrate-and-fire computational model based on the connectome of the entire adult Drosophila brain reveals insights into sensorimotor processing

The forthcoming assembly of the adult Drosophila melanogaster central brain connectome, containing over 125,000 neurons and 50 million synaptic connections, provides a template for examining sensory processing throughout the brain. Here, we create a leaky integrate-and-fire computational model of the entire Drosophila brain, based on neural connectivity and neurotransmitter identity, to study circuit properties of feeding and grooming behaviors. We show that activation of sugar-sensing or water-sensing gustatory neurons in the computational model accurately predicts neurons that respond to tastes and are required for feeding initiation. Computational activation of neurons in the feeding region of the Drosophila brain predicts those that elicit motor neuron firing, a testable hypothesis that we validate by optogenetic activation and behavioral studies. Moreover, computational activation of different classes of gustatory neurons makes accurate predictions of how multiple taste modalities interact, providing circuit-level insight into aversive and appetitive taste processing. Our computational model predicts that the sugar and water pathways form a partially shared appetitive feeding initiation pathway, which our calcium imaging and behavioral experiments confirm. Additionally, we applied this model to mechanosensory circuits and found that computational activation of mechanosensory neurons predicts activation of a small set of neurons comprising the antennal grooming circuit that do not overlap with gustatory circuits, and accurately describes the circuit response upon activation of different mechanosensory subtypes. Our results demonstrate that modeling brain circuits purely from connectivity and predicted neurotransmitter identity generates experimentally testable hypotheses and can accurately describe complete sensorimotor transformations.

Invertebrates as models of learning and memory: investigating neural and molecular mechanisms

In this Commentary, we shed light on the use of invertebrates as model organisms for understanding the causal and conserved mechanisms of learning and memory. We provide a condensed chronicle of the contribution offered by mollusks to the studies on how and where the nervous system encodes and stores memory and describe the rich cognitive capabilities of some insect species, including attention and concept learning. We also discuss the use of planarians for investigating the dynamics of memory during brain regeneration and highlight the role of stressful stimuli in forming memories. Furthermore, we focus on the increasing evidence that invertebrates display some forms of emotions, which provides new opportunities for unveiling the neural and molecular mechanisms underlying the complex interaction between stress, emotions and cognition. In doing so, we highlight experimental challenges and suggest future directions that we expect the field to take in the coming years, particularly regarding what we, as humans, need to know for preventing and/or delaying memory loss. This article has an associated ECR Spotlight interview with Veronica Rivi.

Nonsynaptic Transmission Mediates Light Context-Dependent Odor Responses in Drosophila melanogaster

Recent connectome analyses of the entire synaptic circuit in the nervous system have provided tremendous insights into how neural processing occurs through the synaptic relay of neural information. Conversely, the extent to which ephaptic transmission which does not depend on the synapses contributes to the relay of neural information, especially beyond a distance between adjacent neurons and to neural processing remains unclear. We show that ephaptic transmission mediated by extracellular potential changes in female Drosophila melanogaster can reach >200 µm, equivalent to the depth of its brain. Furthermore, ephaptic transmission driven by retinal photoreceptor cells mediates light-evoked firing rate increases in olfactory sensory neurons. These results indicate that ephaptic transmission contributes to sensory responses that can change momentarily in a context-dependent manner.SIGNIFICANCE STATEMENT Although extracellular field potential activities are commonly observed in many nervous systems, this activity has been generally considered as a side effect of synchronized spiking of neurons. This study, however, shows that field potential changes in retinae evoked by a sensory stimulus can control the excitability of distant neurons in vivo and mediates multimodal sensory integration in Drosophila melanogaster As such ephaptic transmission is more effective at a short distance, the ephaptic transmission from the retinae may contribute significantly to firing rate changes in downstream neurons of the photoreceptor cells in the optic lobe.

Endocrine cybernetics: neuropeptides as molecular switches in behavioural decisions

Plasticity in animal behaviour relies on the ability to integrate external and internal cues from the changing environment and hence modulate activity in synaptic circuits of the brain. This context-dependent neuromodulation is largely based on non-synaptic signalling with neuropeptides. Here, we describe select peptidergic systems in the Drosophila brain that act at different levels of a hierarchy to modulate behaviour and associated physiology. These systems modulate circuits in brain regions, such as the central complex and the mushroom bodies, which supervise specific behaviours. At the top level of the hierarchy there are small numbers of large peptidergic neurons that arborize widely in multiple areas of the brain to orchestrate or modulate global activity in a state and context-dependent manner. At the bottom level local peptidergic neurons provide executive neuromodulation of sensory gain and intrinsically in restricted parts of specific neuronal circuits. The orchestrating neurons receive interoceptive signals that mediate energy and sleep homeostasis, metabolic state and circadian timing, as well as external cues that affect food search, aggression or mating. Some of these cues can be triggers of conflicting behaviours such as mating versus aggression, or sleep versus feeding, and peptidergic neurons participate in circuits, enabling behaviour choices and switches.

A neuromechanical model for Drosophila larval crawling based on physical measurements

BACKGROUND

Animal locomotion requires dynamic interactions between neural circuits, the body (typically muscles), and surrounding environments. While the neural circuitry of movement has been intensively studied, how these outputs are integrated with body mechanics (neuromechanics) is less clear, in part due to the lack of understanding of the biomechanical properties of animal bodies. Here, we propose an integrated neuromechanical model of movement based on physical measurements by taking Drosophila larvae as a model of soft-bodied animals.

RESULTS

We first characterized the kinematics of forward crawling in Drosophila larvae at a segmental and whole-body level. We then characterized the biomechanical parameters of fly larvae, namely the contraction forces generated by neural activity, and passive elastic and viscosity of the larval body using a stress-relaxation test. We established a mathematical neuromechanical model based on the physical measurements described above, obtaining seven kinematic values characterizing crawling locomotion. By optimizing the parameters in the neural circuit, our neuromechanical model succeeded in quantitatively reproducing the kinematics of larval locomotion that were obtained experimentally. This model could reproduce the observation of optogenetic studies reported previously. The model predicted that peristaltic locomotion could be exhibited in a low-friction condition. Analysis of floating larvae provided results consistent with this prediction. Furthermore, the model predicted a significant contribution of intersegmental connections in the central nervous system, which contrasts with a previous study. This hypothesis allowed us to make a testable prediction for the variability in intersegmental connection in sister species of the genus Drosophila.

CONCLUSIONS

We generated a neurochemical model based on physical measurement to provide a new foundation to study locomotion in soft-bodied animals and soft robot engineering.

Analysis of rod/cone gap junctions from the reconstruction of mouse photoreceptor terminals

Electrical coupling, mediated by gap junctions, contributes to signal averaging, synchronization, and noise reduction in neuronal circuits. In addition, gap junctions may also provide alternative neuronal pathways. However, because they are small and especially difficult to image, gap junctions are often ignored in large-scale 3D reconstructions. Here, we reconstruct gap junctions between photoreceptors in the mouse retina using serial blockface-scanning electron microscopy, focused ion beam-scanning electron microscopy, and confocal microscopy for the gap junction protein Cx36. An exuberant spray of fine telodendria extends from each cone pedicle (including blue cones) to contact 40-50 nearby rod spherules at sites of Cx36 labeling, with approximately 50 Cx36 clusters per cone pedicle and 2-3 per rod spherule. We were unable to detect rod/rod or cone/cone coupling. Thus, rod/cone coupling accounts for nearly all gap junctions between photoreceptors. We estimate a mean of 86 Cx36 channels per rod/cone pair, which may provide a maximum conductance of ~1200 pS, if all gap junction channels were open. This is comparable to the maximum conductance previously measured between rod/cone pairs in the presence of a dopamine antagonist to activate Cx36, suggesting that the open probability of gap junction channels can approach 100% under certain conditions.

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

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.

Detecting Square Grid Structure in an Animal Neuronal Network

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.