The brain plans and executes volitional movements. The underlying patterns of neural population activity have been explored in the context of movements of the eyes, limbs, tongue, and head in nonhuman primates and rodents. How do networks of neurons produce the slow neural dynamics that prepare specific movements and the fast dynamics that ultimately initiate these movements? Recent work exploits rapid and calibrated perturbations of neural activity to test specific dynamical systems models that are capable of producing the observed neural activity. These joint experimental and computational studies show that cortical dynamics during motor planning reflect fixed points of neural activity (attractors). Subcortical control signals reshape and move attractors over multiple timescales, causing commitment to specific actions and rapid transitions to movement execution. Experiments in rodents are beginning to reveal how these algorithms are implemented at the level of brain-wide neural circuits.

Taste detection and hunger state dynamically regulate the decision to initiate feeding. To study how context-appropriate feeding decisions are generated, we combined synaptic resolution circuit reconstruction with targeted genetic access to specific neurons to elucidate a gustatory sensorimotor circuit for feeding initiation in Drosophila melanogaster. This circuit connects gustatory sensory neurons to proboscis motor neurons through three intermediate layers. Most of the neurons in this pathway are necessary and sufficient for proboscis extension, a feeding initiation behavior, and respond selectively to sugar taste detection. Hunger signals act at select second-order neurons to increase feeding initiation in food-deprived animals. In contrast, a bitter taste pathway inhibits premotor neurons, illuminating a central mechanism that weighs sugar and bitter tastes to promote or inhibit feeding. Together, these studies reveal the neural circuit basis for the integration of external taste detection and internal nutritive state to flexibly execute a critical feeding decision.

Chemical neurotransmission constitutes one of the fundamental modalities of communication between neurons. Monitoring release of these chemicals has traditionally been difficult to carry out at spatial and temporal scales relevant to neuron function. To understand chemical neurotransmission more fully, we need to improve the spatial and temporal resolutions of measurements for neurotransmitter release. To address this, we engineered a chemi-sensitive, two-dimensional nanofilm that facilitates subcellular visualization of the release and diffusion of the neurochemical dopamine with synaptic resolution, quantal sensitivity, and simultaneously from hundreds of release sites. Using this technology, we were able to monitor the spatiotemporal dynamics of dopamine release in dendritic processes, a poorly understood phenomenon. We found that dopamine release is broadcast from a subset of dendritic processes as hotspots that have a mean spatial spread of ≈3.2 µm (full width at half maximum) and are observed with a mean spatial frequency of 1 hotspot per ≈7.5 µm of dendritic length. Major dendrites of dopamine neurons and fine dendritic processes, as well as dendritic arbors and dendrites with no apparent varicose morphology participated in dopamine release. Remarkably, these release hotspots colocalized with Bassoon, suggesting that Bassoon may contribute to organizing active zones in dendrites, similar to its role in axon terminals.

The development of enzyme-based self-labeling tags allow the labeling of proteins in living cells with synthetic small-molecules. Use of a fluorophore-containing ligand enables the visualization of protein location inside cells using fluorescence microscopy. Alternatively, deployment of a biotin-containing ligand allows purification of tagged protein using affinity resins. Despite these various applications of self-labeling tags, most ligands serve a single purpose. Here, we describe self-labeling tag ligands that allow both visualization and subsequent capture of a protein. A key design principle is exploiting the chemical properties and size of a rhodamine fluorophore to optimize cell-permeability of the ligand and the capture efficiency of the biotin conjugate. This work generates useful “multifunctional” fluorophores with generalizable design principles that will allow the construction of new tools for biology.

How pioneer factors interface with chromatin to promote accessibility for transcription control is poorly understood in vivo. Here, we directly visualize chromatin association by the prototypical GAGA pioneer factor (GAF) in live Drosophila hemocytes. Single-particle tracking reveals that most GAF is chromatin bound, with a stable-binding fraction showing nucleosome-like confinement residing on chromatin for more than 2 min, far longer than the dynamic range of most transcription factors. These kinetic properties require the full complement of GAF's DNA-binding, multimerization and intrinsically disordered domains, and are autonomous from recruited chromatin remodelers NURF and PBAP, whose activities primarily benefit GAF's neighbors such as Heat Shock Factor. Evaluation of GAF kinetics together with its endogenous abundance indicates that, despite on-off dynamics, GAF constitutively and fully occupies major chromatin targets, thereby providing a temporal mechanism that sustains open chromatin for transcriptional responses to homeostatic, environmental and developmental signals.

Hundreds of millions of structured proteins sustain life through chemical interactions and catalytic reactions1. Though dynamic, these proteins are assumed to be built upon fixed scaffolds of secondary structure, α-helices and β-sheets. Experimentally determined structures of over >58,000 non-redundant proteins support this assumption, though it has recently been challenged by ∼100 fold-switching proteins2. These “metamorphic3” proteins, though ostensibly rare, raise the question of how many uncharacterized proteins have shapeshifting–rather than fixed–secondary structures. To address this question, we developed a comparative sequence-based approach that predicts fold-switching proteins from differences in secondary structure propensity. We applied this approach to the universally conserved NusG transcription factor family of ∼15,000 proteins, one of which has a 50-residue regulatory subunit experimentally shown to switch between α-helical and β-sheet folds4. Our approach predicted that 25% of the sequences in this family undergo similar α-helix ⇌ β-sheet transitions, a frequency two orders of magnitude larger than previously observed. Our predictions evade state-of-the-art computational methods but were confirmed experimentally by circular dichroism and nuclear magnetic resonance spectroscopy for all 10 assiduously chosen dissimilar variants. These results suggest that fold switching is a pervasive mechanism of transcriptional regulation in all kingdoms of life and imply that numerous uncharacterized proteins may also switch folds.

Wistar-Kyoto (WKY) rats as an endogenous depression model partially lack a response to classic selective serotonin reuptake inhibitors (SSRIs). Thus, this strain has the potential to be established as a model of treatment-resistant depression (TRD). However, the SSRI resistance in WKY rats is still not fully understood. In this study, WKY and control rats were subjected to a series of tests, namely, a forced swim test (FST), a sucrose preference test (SPT), and an open field test (OFT), and were scanned in a 7.0-T MRI scanner before and after three-week citalopram or saline administration. Behavioral results demonstrated that WKY rats had increased immobility in the FST and decreased sucrose preference in the SPT and central time spent in the OFT. However, citalopram did not improve immobility in the FST. The amplitude of low-frequency fluctuation (ALFF) analysis showed regional changes in the striatum and hippocampus of WKY rats. However, citalopram partially reversed the ALFF value in the dorsal part of the two regions. Functional connectivity (FC) analysis showed that FC strengths were decreased in WKY rats compared with controls. Nevertheless, citalopram partially increased FC strengths in WKY rats. Based on FC, global graph analysis demonstrated decreased network efficiency in WKY + saline group compared with control + saline group, but citalopram showed weak network efficiency improvement. In conclusion, resting-state fMRI results implied widely affected brain function at both regional and global levels in WKY rats. Citalopram had only partial effects on these functional changes, indicating a potential treatment resistance mechanism.

The PV2 (Celio 1990), a cluster of parvalbumin-positive neurons located in the ventromedial region of the distal periaqueductal gray (PAG) has not been previously described as its own entity, leading us to study its extent, connections, and gene expression. It is an oval, bilateral, elongated cluster composed of approximately 475 parvalbumin-expressing neurons in a single mouse hemisphere. In its anterior portion it impinges upon the paratrochlear nucleus (Par4) and in its distal portion it is harbored in the posterodorsal raphe nucleus (PDR). It is known to receive inputs from the orbitofrontal cortex and from the parvafox nucleus in the ventrolateral hypothalamus. Using anterograde tracing methods in parvalbumin-Cre mice, the main projections of the PV2 cluster innervate the supraoculomotor periaqueductal gray (Su3) of the PAG, the parvafox nucleus of the lateral hypothalamus, the gemini nuclei of the posterior hypothalamus, the septal regions, and the diagonal band in the forebrain, as well as various nuclei within the reticular formation in the midbrain and brainstem. Within the brainstem, projections were discrete, but involved areas implicated in autonomic control. The PV2 cluster expressed various peptides and receptors, including the receptor for Adcyap1, a peptide secreted by one of its main afferences, namely, the parvafox nucleus. The expression of GAD1 and GAD2 in the region of the PV2, the presence of Vgat-1 in a subpopulation of PV2-neurons as well as the coexistence of GAD67 immunoreactivity with parvalbumin in terminal endings indicates the inhibitory nature of a subpopulation of PV2-neurons. The PV2 cluster may be part of a feedback controlling the activity of the hypothalamic parvafox and the Su3 nuclei in the periaqueductal gray.

Neural computation in biological and artificial networks relies on nonlinear synaptic integration. The structural connectivity matrix of synaptic weights between neurons is a critical determinant of overall network function. However, quantitative links between neural network structure and function are complex and subtle. For example, many networks can give rise to similar functional responses, and the same network can function differently depending on context. Whether certain patterns of synaptic connectivity are required to generate specific network-level computations is largely unknown. Here we introduce a geometric framework for identifying synaptic connections required by steady-state responses in recurrent networks of rectified-linear neurons. Assuming that the number of specified response patterns does not exceed the number of input synapses, we analytically calculate all feedforward and recurrent connectivity matrices that can generate the specified responses from the network inputs. We then use this analytical characterization to rigorously analyze the solution space geometry and derive certainty conditions guaranteeing a non-zero synapse between neurons. Numerical simulations of feedforward and recurrent networks verify our analytical results. Our theoretical framework could be applied to neural activity data to make anatomical predictions that follow generally from the model architecture. It thus provides novel opportunities for discerning what model features are required to accurately relate neural network structure and function.

Task-related neural activity is widespread across populations of neurons during goal-directed behaviors. However, little is known about the synaptic reorganization and circuit mechanisms that lead to broad activity changes. Here we trained a limited subset of neurons in a spiking network with strong synaptic interactions to reproduce the activity of neurons in the motor cortex during a decision-making task. We found that task-related activity, resembling the neural data, emerged across the network, even in the untrained neurons. Analysis of trained networks showed that strong untrained synapses, which were independent of the task and determined the dynamical state of the network, mediated the spread of task-related activity. Optogenetic perturbations suggest that the motor cortex is strongly-coupled, supporting the applicability of the mechanism to cortical networks. Our results reveal a cortical mechanism that facilitates distributed representations of task-variables by spreading the activity from a subset of plastic neurons to the entire network through task-independent strong synapses.