Prostaglandin E2 Induces Long-Lasting Inhibition of Noradrenergic Neurons in the Locus Coeruleus and Moderates the Behavioral Response to Stressors.

Neuronal activity is modulated not only by inputs from other neurons but also by various factors, such as bioactive substances. Noradrenergic (NA) neurons in the locus coeruleus (LC-NA neurons) are involved in diverse physiological functions, including sleep/wakefulness and stress responses. Previous studies have identified various substances and receptors that modulate LC-NA neuronal activity through techniques including electrophysiology, calcium imaging, and single-cell RNA sequencing. However, many substances with unknown physiological significance have been overlooked. Here, we established an efficient screening method for identifying substances that modulate LC-NA neuronal activity through intracellular calcium ([Ca2+]i) imaging using brain slices. Using both sexes of mice, we screened 53 bioactive substances, and identified five novel substances: gastrin-releasing peptide, neuromedin U, and angiotensin II, which increase [Ca2+]i, and pancreatic polypeptide and prostaglandin D2, which decrease [Ca2+]i Among them, neuromedin U induced the greatest response in female mice. In terms of the duration of [Ca2+]i change, we focused on prostaglandin E2 (PGE2), since it induces a long-lasting decrease in [Ca2+]i via the EP3 receptor. Conditional knock-out of the receptor in LC-NA neurons resulted in increased depression-like behavior, prolonged wakefulness in the dark period, and increased [Ca2+]i after stress exposure. Our results demonstrate the effectiveness of our screening method for identifying substances that modulate a specific neuronal population in an unbiased manner and suggest that stress-induced prostaglandin E2 can suppress LC-NA neuronal activity to moderate the behavioral response to stressors. Our screening method will contribute to uncovering previously unknown physiological functions of uncharacterized bioactive substances in specific neuronal populations.SIGNIFICANCE STATEMENT Bioactive substances modulate the activity of specific neuronal populations. However, since only a limited number of substances with predicted effects have been investigated, many substances that may modulate neuronal activity have gone unrecognized. Here, we established an unbiased method for identifying modulatory substances by measuring the intracellular calcium signal, which reflects neuronal activity. We examined noradrenergic (NA) neurons in the locus coeruleus (LC-NA neurons), which are involved in diverse physiological functions. We identified five novel substances that modulate LC-NA neuronal activity. We also found that stress-induced prostaglandin E2 (PGE2) may suppress LC-NA neuronal activity and influence behavioral outcomes. Our screening method will help uncover previously overlooked functions of bioactive substances and provide insight into unrecognized roles of specific neuronal populations.

Growth and splitting of neural sequences in songbird vocal development.

Neural sequences are a fundamental feature of brain dynamics underlying diverse behaviours, but the mechanisms by which they develop during learning remain unknown. Songbirds learn vocalizations composed of syllables; in adult birds, each syllable is produced by a different sequence of action potential bursts in the premotor cortical area HVC. Here we carried out recordings of large populations of HVC neurons in singing juvenile birds throughout learning to examine the emergence of neural sequences. Early in vocal development, HVC neurons begin producing rhythmic bursts, temporally locked to a 'prototype' syllable. Different neurons are active at different latencies relative to syllable onset to form a continuous sequence. Through development, as new syllables emerge from the prototype syllable, initially highly overlapping burst sequences become increasingly distinct. We propose a mechanistic model in which multiple neural sequences can emerge from the growth and splitting of a common precursor sequence.

Group-common and individual-specific effects of structure-function coupling in human brain networks with graph neural networks.

The human cerebral cortex is organized into functionally segregated but synchronized regions bridged by the structural connectivity of white matter pathways. While structure-function coupling has been implicated in cognitive development and neuropsychiatric disorders, studies yield inconsistent findings. The extent to which the structure-function coupling reflects reliable individual differences or primarily group-common characteristics remains unclear, at both the global and regional brain levels. By leveraging two independent, high-quality datasets, we found that the graph neural network accurately predicted unseen individuals' functional connectivity from structural connectivity, reflecting a strong structure-function coupling. This coupling was primarily driven by network topology and was substantially stronger than that of the linear models. Moreover, we observed that structure-function coupling was dominated by group-common effects, with subtle yet significant individual-specific effects. The regional group and individual effects of coupling were hierarchically organized across the cortex along a sensorimotor-association axis, with lower group and higher individual effects in association cortices. These findings emphasize the importance of considering both group and individual effects in understanding cortical structure-function coupling, suggesting insights into interpreting individual differences of the coupling and informing connectivity-guided therapeutics.

A Neural Network for Wind-Guided Compass Navigation.

Spatial maps in the brain are most accurate when they are linked to external sensory cues. Here, we show that the compass in the Drosophila brain is linked to the direction of the wind. Shifting the wind rightward rotates the compass as if the fly were turning leftward, and vice versa. We describe the mechanisms of several computations that integrate wind information into the compass. First, an intensity-invariant representation of wind direction is computed by comparing left-right mechanosensory signals. Then, signals are reformatted to reduce the coding biases inherent in peripheral mechanics, and wind cues are brought into the same circular coordinate system that represents visual cues and self-motion signals. Because the compass incorporates both mechanosensory and visual cues, it should enable navigation under conditions where no single cue is consistently reliable. These results show how local sensory signals can be transformed into a global, multimodal, abstract representation of space.

Rhythmic Continuous-Time Coding in the Songbird Analog of Vocal Motor Cortex.

Songbirds learn and produce complex sequences of vocal gestures. Adult birdsong requires premotor nucleus HVC, in which projection neurons (PNs) burst sparsely at stereotyped times in the song. It has been hypothesized that PN bursts, as a population, form a continuous sequence, while a different model of HVC function proposes that both HVC PN and interneuron activity is tightly organized around motor gestures. Using a large dataset of PNs and interneurons recorded in singing birds, we test several predictions of these models. We find that PN bursts in adult birds are continuously and nearly uniformly distributed throughout song. However, we also find that PN and interneuron firing rates exhibit significant 10-Hz rhythmicity locked to song syllables, peaking prior to syllable onsets and suppressed prior to offsets-a pattern that predominates PN and interneuron activity in HVC during early stages of vocal learning.

In vivo recording of single-unit activity during singing in zebra finches.

The zebra finch is an important model for investigating the neural mechanisms that underlie vocal production and learning. Previous anatomical and gene expression studies have identified an interconnected set of brain areas in this organism that are important for singing. To advance our understanding of how these various brain areas act together to learn and produce a highly stereotyped song, it is necessary to record the activity of individual neurons during singing. Here, we present a protocol for recording single-unit activity in freely moving zebra finches during singing using a miniature, motorized microdrive. It includes procedures for both the microdrive implant surgery and the electrophysiological recordings. There are several advantages of this technique: (1) high-impedance electrodes can be used in the microdrive to obtain well-isolated single units; (2) a motorized microdrive is used to remotely control the electrode position, allowing neurons to be isolated without handling the bird, and (3) a lateral positioner is used to move electrodes into fresh tissue before each penetration, allowing recordings from well-isolated neurons over the course of several weeks. We also describe the application of the antidromic stimulation and the spike collision test to identify neurons based on the axonal projection patterns.