In insects, the neuropeptide eclosion hormone (EH) acts on the CNS to evoke the stereotyped behaviors that cause ecdysis, the shedding of the cuticle at the end of each molt. Concomitantly, EH induces an increase in cyclic GMP (cGMP). Using antibodies against this second messenger, we show that this increase is confined to a network of 50 peptidergic neurons distributed throughout the CNS. Increases appeared 30 min after EH treatment, spread rapidly throughout these neurons, and were extremely long lived. We show that this response is synaptically driven, and does not involve the soluble, nitric oxide (NO)-activated, guanylate cyclase. Stereotyped variations in the duration of the cGMP response among neurons suggest a role in coordinating responses having different latencies and durations.

Measuring the dynamics of neural processing across time scales requires following the spiking of thousands of individual neurons over milliseconds and months. To address this need, we introduce the Neuropixels 2.0 probe together with newly designed analysis algorithms. The probe has more than 5000 sites and is miniaturized to facilitate chronic implants in small mammals and recording during unrestrained behavior. High-quality recordings over long time scales were reliably obtained in mice and rats in six laboratories. Improved site density and arrangement combined with newly created data processing methods enable automatic post hoc correction for brain movements, allowing recording from the same neurons for more than 2 months. These probes and algorithms enable stable recordings from thousands of sites during free behavior, even in small animals such as mice.

Although CMOS fabrication has enabled a quick evolution in the design of high-density neural probes and neural-recording chips, the scaling and miniaturization of the complete data-acquisition systems has happened at a slower pace. This is mainly due to the complexity and the many requirements that change depending on the specific experimental settings. In essence, the fundamental challenge of a neural-recording system is getting the signals describing the largest possible set of neurons out of the brain and down to data storage for analysis. This requires a complete system optimization that considers the physical, electrical, thermal and signal-processing requirements, while accounting for available technology, manufacturing constraints and budget. Here we present a scalable and open-standards-based open-source data-acquisition system capable of recording from over 10,000 channels of raw neural data simultaneously. The components and their interfaces have been optimized to ensure robustness and minimum invasiveness in small-rodent electrophysiology.

High-resolution extracellular electrophysiology is the gold standard for recording spikes from distributed neural populations, and is especially powerful when combined with optogenetics for manipulation of specific cell types with high temporal resolution. We integrated these approaches into prototype Neuropixels Opto probes, which combine electronic and photonic circuits. These devices pack 960 electrical recording sites and two sets of 14 light emitters onto a 1 cm shank, allowing spatially addressable optogenetic stimulation with blue and red light. In mouse cortex, Neuropixels Opto probes delivered high-quality recordings together with spatially addressable optogenetics, differentially activating or silencing neurons at distinct cortical depths. In mouse striatum and other deep structures, Neuropixels Opto probes delivered efficient optotagging, facilitating the identification of two cell types in parallel. Neuropixels Opto probes represent an unprecedented tool for recording, identifying, and manipulating neuronal populations.

Neuroscientists are now able to acquire data at staggering rates across spatiotemporal scales. However, our ability to capitalize on existing datasets, tools, and intellectual capacities is hampered by technical challenges. The key barriers to accelerating scientific discovery correspond to the FAIR data principles: findability, global access to data, software interoperability, and reproducibility/re-usability. We conducted a hackathon dedicated to making strides in those steps. This manuscript is a technical report summarizing these achievements, and we hope serves as an example of the effectiveness of focused, deliberate hackathons towards the advancement of our quickly-evolving field.

The accumulation of amyloid-beta (Abeta) into plaques is a hallmark feature of Alzheimer’s disease (AD). While amyloid precursor protein (APP)-related proteins are found in most organisms, only Abeta fragments from human APP have been shown to induce amyloid deposits and progressive neurodegeneration. Therefore, it was suggested that neurotoxic effects are a specific property of human Abeta. Here we show that Abeta fragments derived from the Drosophila orthologue APPL aggregate into intracellular fibrils, amyloid deposits, and cause age-dependent behavioral deficits and neurodegeneration. We also show that APPL can be cleaved by a novel fly beta-secretase-like enzyme. This suggests that Abeta-induced neurotoxicity is a conserved function of APP proteins whereby the lack of conservation in the primary sequence indicates that secondary structural aspects determine their pathogenesis. In addition, we found that the behavioral phenotypes precede extracellular amyloid deposit formation, supporting results that intracellular Abeta plays a key role in AD.

High-resolution electron microscopy of nervous systems has enabled the reconstruction of synaptic connectomes. However, we do not know the synaptic sign for each connection (i.e., whether a connection is excitatory or inhibitory), which is implied by the released transmitter. We demonstrate that artificial neural networks can predict transmitter types for presynapses from electron micrographs: a network trained to predict six transmitters (acetylcholine, glutamate, GABA, serotonin, dopamine, octopamine) achieves an accuracy of 87% for individual synapses, 94% for neurons, and 91% for known cell types across a D. melanogaster whole brain. We visualize the ultrastructural features used for prediction, discovering subtle but significant differences between transmitter phenotypes. We also analyze transmitter distributions across the brain and find that neurons that develop together largely express only one fast-acting transmitter (acetylcholine, glutamate, or GABA). We hope that our publicly available predictions act as an accelerant for neuroscientific hypothesis generation for the fly.

The vast majority of the adult fly ventral nerve cord is composed of 34 hemilineages, which are clusters of lineally related neurons. Neurons in these hemilineages use one of the three fast-acting neurotransmitters (acetylcholine, GABA, or glutamate) for communication. We generated a comprehensive neurotransmitter usage map for the entire ventral nerve cord. We did not find any cases of neurons using more than one neurotransmitter, but found that the acetylcholine specific gene ChAT is transcribed in many glutamatergic and GABAergic neurons, but these transcripts typically do not leave the nucleus and are not translated. Importantly, our work uncovered a simple rule: All neurons within a hemilineage use the same neurotransmitter. Thus, neurotransmitter identity is acquired at the stem cell level. Our detailed transmitter- usage/lineage identity map will be a great resource for studying the developmental basis of behavior and deciphering how neuronal circuits function to regulate behavior.