Incentives tend to drive improvements in performance. But when incentives get too high, we can “choke under pressure” and underperform when it matters most. What neural processes might lead to choking under pressure? We studied Rhesus monkeys performing a challenging reaching task in which they underperform when an unusually large “jackpot” reward is at stake. We observed a collapse in neural information about upcoming movements for jackpot rewards: in the motor cortex, neural planning signals became less distinguishable for different reach directions when a jackpot reward was made available. We conclude that neural signals of reward and motor planning interact in the motor cortex in a manner that can explain why we choke under pressure.

The C9orf72 hexanucleotide repeat expansion (HRE) is the most frequent genetic cause of the neurodegenerative diseases amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD). Here, we describe the pathogenic cascades that are initiated by the C9orf72 HRE DNA. The HRE DNA binds to its protein partner DAXX and promotes its liquid-liquid phase separation, which is capable of reorganizing genomic structures. An HRE-dependent nuclear accumulation of DAXX drives chromatin remodeling and epigenetic changes such as histone hypermethylation and hypoacetylation in patient cells. While regulating global gene expression, DAXX plays a key role in the suppression of basal and stress-inducible expression of C9orf72 via chromatin remodeling and epigenetic modifications of the promoter of the major C9orf72 transcript. Downregulation of DAXX or rebalancing the epigenetic modifications mitigates the stress-induced sensitivity of C9orf72-patient-derived motor neurons. These studies reveal a C9orf72 HRE DNA-dependent regulatory mechanism for both local and genomic architectural changes in the relevant diseases.

Forces controlling tissue morphogenesis are attributed to cellular-driven activities, and any role for extracellular matrix (ECM) is assumed to be passive. However, all polymer networks, including ECM, can develop autonomous stresses during their assembly. Here, we examine the morphogenetic function of an ECM before reaching homeostatic equilibrium by analyzing de novo ECM assembly during Drosophila ventral nerve cord (VNC) condensation. Asymmetric VNC shortening and a rapid decrease in surface area correlate with the exponential assembly of collagen IV (Col4) surrounding the tissue. Concomitantly, a transient developmentally induced Col4 gradient leads to coherent long-range flow of ECM, which equilibrates the Col4 network. Finite element analysis and perturbation of Col4 network formation through the generation of dominant Col4 mutations that affect assembly reveal that VNC morphodynamics is partially driven by a sudden increase in ECM-driven surface tension. These data suggest that ECM assembly stress and associated network instabilities can actively participate in tissue morphogenesis.

How do developing neurons select their synaptic partners? To identify molecules matching synaptic partners, we integrated the synapse-level connectome of neural circuits with the developmental expression patterns and binding specificities of cell adhesion molecules (CAMs) on pre- and postsynaptic neurons. We focused on parallel synaptic pathways in the Drosophila visual system, in which closely related neurons form synapses onto closely related target neurons. We show that the choice of synaptic partners correlates with the matching expression of receptor-ligand pairs of Beat and Side proteins of the immunoglobulin superfamily (IgSF) CAMs. Genetic analysis demonstrates that these proteins determine the choice between alternative synaptic targets. Combining transcriptomes, connectomes, and protein interactome maps provides a framework to uncover the molecular logic of synaptic connectivity.

The hippocampus is critical for recollecting and imagining experiences. This is believed to involve voluntarily drawing from hippocampal memory representations of people, events, and places, including the hippocampus’ map-like representations of familiar environments. However, whether the representations in such “cognitive maps” can be volitionally and selectively accessed is unknown. We developed a brain-machine interface to test if rats could control their hippocampal activity in a flexible, goal-directed, model-based manner. We show that rats can efficiently navigate or direct objects to arbitrary goal locations within a virtual reality arena solely by activating and sustaining appropriate hippocampal representations of remote places. This should provide insight into the mechanisms underlying episodic memory recall, mental simulation/planning, and imagination, and open up possibilities for high-level neural prosthetics utilizing hippocampal representations.

Healthy mitochondria are critical for reproduction. During aging, both reproductive fitness and mitochondrial homeostasis decline. Mitochondrial metabolism and dynamics are key factors in supporting mitochondrial homeostasis. However, how they are coupled to control reproductive health remains unclear. We report that mitochondrial GTP metabolism acts through mitochondrial dynamics factors to regulate reproductive aging. We discovered that germline-only inactivation of GTP- but not ATP-specific succinyl-CoA synthetase (SCS), promotes reproductive longevity in Caenorhabditis elegans. We further revealed an age-associated increase in mitochondrial clustering surrounding oocyte nuclei, which is attenuated by the GTP-specific SCS inactivation. Germline-only induction of mitochondrial fission factors sufficiently promotes mitochondrial dispersion and reproductive longevity. Moreover, we discovered that bacterial inputs affect mitochondrial GTP and dynamics factors to modulate reproductive aging. These results demonstrate the significance of mitochondrial GTP metabolism in regulating oocyte mitochondrial homeostasis and reproductive longevity and reveal mitochondrial fission induction as an effective strategy to improve reproductive health.

Proteins localized at the cellular interface mediate cell-cell communication and thus control many aspects of physiology in multicellular organisms. Cell-surface proteomics allows biologists to comprehensively identify proteins on the cell surface and survey their dynamics in physiological and pathological conditions. PEELing provides an integrated package and user-centric web service for analyzing cell-surface proteomics data. With a streamlined and automated workflow, PEELing evaluates data quality using curated references, performs cutoff analysis to remove contaminants, connects to databases for functional annotation, and generates data visualizations. Together with chemical and transgenic tools, PEELing completes a pipeline making cell-surface proteomics analysis handy for every lab.

A prominent trend in single-cell transcriptomics is providing spatial context alongside a characterization of each cell's molecular state. This typically requires targeting an a priori selection of genes, often covering less than 1% of the genome, and a key question is how to optimally determine the small gene panel. We address this challenge by introducing a flexible deep learning framework, PERSIST, to identify informative gene targets for spatial transcriptomics studies by leveraging reference scRNA-seq data. Using datasets spanning different brain regions, species, and scRNA-seq technologies, we show that PERSIST reliably identifies panels that provide more accurate prediction of the genome-wide expression profile, thereby capturing more information with fewer genes. PERSIST can be adapted to specific biological goals, and we demonstrate that PERSIST's binarization of gene expression levels enables models trained on scRNA-seq data to generalize with to spatial transcriptomics data, despite the complex shift between these technologies.

The endoplasmic reticulum (ER) is a structurally complex, membrane-enclosed compartment that stretches from the nuclear envelope to the extreme periphery of eukaryotic cells. The organelle is crucial for numerous distinct cellular processes, but how these processes are spatially regulated within the structure is unclear. Traditional imaging-based approaches to understanding protein dynamics within the organelle are limited by the convoluted structure and rapid movement of molecular components. Here, we introduce a combinatorial imaging and machine learning-assisted image analysis approach to track the motion of photoactivated proteins within the ER of live cells. We find that simultaneous knowledge of the underlying ER structure is required to accurately analyze fluorescently-tagged protein redistribution, and after appropriate structural calibration we see all proteins assayed show signatures of Brownian diffusion-dominated motion over micron spatial scales. Remarkably, we find that in some cells the ER structure can be explored in a highly asymmetric manner, likely as a result of uneven connectivity within the organelle. This remains true independently of the size, topology, or folding state of the fluorescently-tagged molecules, suggesting a potential role for ER connectivity in driving spatially regulated biology in eukaryotes.

PURPOSE: To develop an algorithm and scripts to combine disparate multimodal imaging modalities and show its use by overlaying en-face optical coherence tomography angiography (OCTA) images and Optos ultra-widefield (UWF) retinal images using the Fiji (ImageJ) plugin BigWarp.

METHODS: Optos UWF images and Heidelberg en-face OCTA images were collected from various patients as part of their routine care. En-face OCTA images were generated and ten (10) images at varying retinal depths were exported. The Fiji plugin BigWarp was used to transform the Optos UWF image onto the en-face OCTA image using matching reference points in the retinal vasculature surrounding the macula. The images were then overlayed and stacked to create a series of ten combined Optos UWF and en-face OCTA images of increasing retinal depths. The first algorithm was modified to include two scripts that automatically aligned all the en-face OCTA images.

RESULTS: The Optos UWF image could easily be transformed to the en-face OCTA images using BigWarp with common vessel branch point landmarks in the vasculature. The resulting warped Optos image was then successfully superimposed onto the ten Optos UWF images. The scripts more easily allowed for automatic overlay of the images.

CONCLUSIONS: Optos UWF images can be successfully superimposed onto en-face OCTA images using freely available software that has been applied to ocular use. This synthesis of multimodal imaging may increase their potential diagnostic value. Script A is publicly available at https://doi.org/10.6084/m9.figshare.16879591.v1 and Script B is available at https://doi.org/10.6084/m9.figshare.17330048.