Homeostasis is a biological principle for regulation of essential physiological parameters within a set range. Behavioural responses due to deviation from homeostasis are critical for survival, but motivational processes engaged by physiological need states are incompletely understood. We examined motivational characteristics of two separate neuron populations that regulate energy and fluid homeostasis by using cell-type-specific activity manipulations in mice. We found that starvation-sensitive AGRP neurons exhibit properties consistent with a negative-valence teaching signal. Mice avoided activation of AGRP neurons, indicating that AGRP neuron activity has negative valence. AGRP neuron inhibition conditioned preference for flavours and places. Correspondingly, deep-brain calcium imaging revealed that AGRP neuron activity rapidly reduced in response to food-related cues. Complementary experiments activating thirst-promoting neurons also conditioned avoidance. Therefore, these need-sensing neurons condition preference for environmental cues associated with nutrient or water ingestion, which is learned through reduction of negative-valence signals during restoration of homeostasis.

In insects, the shedding of the old cuticle at the end of a molt involves a stereotyped sequence of distinct behaviors. Our studies on the isolated nervous system of Manduca sexta show that the peptides ecdysis-triggering hormone (ETH) and crustacean cardioactive peptide (CCAP) elicit the first two motor behaviors, the pre-ecdysis and ecdysis behaviors, respectively. Exposing isolated abdominal ganglia to ETH resulted in the generation of sustained pre-ecdysis bursts. By contrast, exposing the entire isolated CNS to ETH resulted in the sequential appearance of pre-ecdysis and ecdysis motor outputs. Previous research has shown that ETH activates neurons within the brain that then release eclosion hormone within the CNS. The latter elevates cGMP levels within and increases the excitability of a group of neurons containing CCAP. In our experiments, the ETH-induced onset of ecdysis bursts was always associated with a rise in intracellular cGMP within these CCAP neurons. We also found that CCAP immunoreactivity decreases centrally during normal ecdysis. Isolated, desheathed abdominal ganglia responded to CCAP by generating rhythmical ecdysis bursts. These ecdysis motor bursts persisted as long as CCAP was present and could be reinduced by successive application of the peptide. CCAP exposure also actively terminated pre-ecdysis bursts from the abdominal CNS, even in the continued presence of ETH. Thus, the sequential performance of the two behaviors arises from one modulator activating the first behavior and also initiating the release of the second modulator. The second modulator then turns off the first behavior while activating the second.

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.

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.