A mathematical model explains saturating axon guidance responses to molecular gradients

Similar Computational Hierarchies for Reading and Speech in the Occipital Cortex of Sighed and Blind: Converging Evidence from fMRI and Chronometric TMS

High-level perception results from interactions between hierarchical brain systems responsive to gradually increasing feature complexities. During reading, the initial evaluation of simple visual features in the early visual cortex (EVC) is followed by orthographic and lexical computations in the ventral occipitotemporal cortex (vOTC). While similar visual regions are engaged in tactile Braille reading in congenitally blind people, it is unclear whether the visual network maintains or reorganizes its hierarchy for reading in this population. Combining fMRI and chronometric transcranial magnetic stimulation (TMS), our study revealed a clear correspondence between sighted and blind individuals (both male and female) on how their occipital cortices functionally supports reading and speech processing. Using fMRI, we first observed that vOTC, but not EVC, showed an enhanced response to lexical vs nonlexical information in both groups and sensory modalities. Using TMS, we further found that, in both groups, the processing of written words and pseudowords was disrupted by the EVC stimulation at both early and late time windows. In contrast, the vOTC stimulation disrupted the processing of these written stimuli only when applied at late time windows, again in both groups. In the speech domain, we observed TMS effects only for meaningful words and only in the blind participants. Overall, our results suggest that, while the responses in the deprived visual areas might extend their functional response to other sensory modalities, the computational gradients between early and higher-order occipital regions are retained, at least for reading.

Phenylhydrazone-based Endoplasmic Reticulum Proteostasis Regulator Compounds with Enhanced Biological Activity

Pharmacological enhancement of endoplasmic reticulum (ER) proteostasis is an attractive strategy to mitigate pathology linked to etiologically-diverse protein misfolding diseases. However, despite this promise, few compounds have been identified that enhance ER proteostasis through defined mechanisms of action. We previously identified the phenylhydrazone-based compound AA263 as a compound that promotes adaptive ER proteostasis remodeling through mechanisms including activation of the ATF6 signaling arm of the unfolded protein response (UPR). However, the protein target(s) of AA263 and the potential for further development of this class of ER proteostasis regulators had not been previously explored. Here, we employ chemical proteomics to demonstrate that AA263 covalently targets a subset of ER protein disulfide isomerases, revealing a molecular mechanism for the activation of ATF6 afforded by this compound. We then use medicinal chemistry to establish next-generation AA263 analogs showing improved potency and efficacy for ATF6 activation, as compared to the parent compound. Finally, we show that treatment with these AA263 analogs enhances secretory pathway proteostasis to correct the pathologic protein misfolding and trafficking of both a destabilized, disease-associated α1-antitrypsin (A1AT) variant and an epilepsy-associated GABA A receptor variant. These results establish AA263 analogs with enhanced potential for correcting imbalanced ER proteostasis associated with etiologically-diverse protein misfolding disorders.

Differential control of growth and identity by HNF4α isoforms in pancreatic ductal adenocarcinoma

Background

Although transcriptomic studies have stratified pancreatic ductal adenocarcinoma (PDAC) into clinically relevant subtypes, classical or basal-like, further research is needed to identify the transcriptional regulators of each subtype. Previous studies identified HNF4α as a key regulator of the classical subtype, but the distinct contributions of its isoforms (P1 and P2), which display dichotomous functions in normal development and gastrointestinal malignancies, remain unexplored.

Objective

The objective of this study is to investigate the role of HNF4α P1 and P2 isoforms in regulating growth and differentiation.

Design

We performed functional, transcriptomic, and epigenetic analysis after exogenous expression in HNF4α-negative models or CRISPRi-mediated knockdown of endogenous isoforms.

Results

We characterized the variable expression of P1 isoforms in HNF4α-positive tumors. We demonstrate that P1 isoforms are less compatible with growth than P2 isoforms. Despite sharing a common DNA binding domain, we show that P1 isoforms are stronger transcriptional regulators.

Conclusions

Our study characterizes the functional roles of HNF4α P1 and P2 isoforms in PDAC and highlights the necessity of considering different isoforms when studying molecular regulators.

Tonotopic Specialization of MYO7A Isoforms in Auditory Hair Cells

1. Mutations in Myo7a cause Usher syndrome type 1B and non-syndromic deafness, but the precise function of MYO7A in sensory hair cells remains unclear. We identify and characterize a novel isoform, MYO7A-N, expressed in auditory hair cells alongside the canonical MYO7A-C. Isoform-specific knock-in mice reveal that inner hair cells primarily express MYO7A-C, while outer hair cells express both isoforms in opposing tonotopic gradients. Both localize to the upper tip-link insertion site, consistent with a role in the tip link for mechanotransduction. Loss of MYO7A-N leads to outer hair cell degeneration and progressive hearing loss. Cryo-EM structures reveal isoform-specific differences at actomyosin interfaces, correlating with distinct ATPase activities. These findings reveal an unexpected layer of molecular diversity within the mechanotransduction machinery. We propose that MYO7A isoform specialization enables fine-tuning of tip-link tension, thus hearing sensitivity, and contributes to the frequency-resolving power of the cochlea.

Time Varying Encoding of Grasping Type and Force in the Primate Motor Cortex

The primary motor cortex (M1) is strongly engaged by movement planning and execution. However, the role of M1 activity in voluntary grasping is still not completely understood. Here we analyze recordings of M1 neurons during the execution of a delayed reach-to-grasp task, where monkeys had to actively grasp an object with either a side or a precision grip, and then pull it with a low or high amount of force. Single cell and neural populations analyses showed that grip type was robustly and specifically encoded by a large population of neurons, while force level was weakly and transiently encoded within mixed-selective neurons that also encoded grip type. Notably, the grip type was stably decoded from motor cortical populations during the preparation and execution epochs of the task. Our results are consistent with the idea that planning and performing specific grasping movements are high-level skills that strongly engage M1 neurons, while the execution of pulling force might be prominently encoded at lower stages of the motor system.

Inference and visualization of complex genotype-phenotype maps with gpmap-tools

Multiplex assays of variant effect (MAVEs) allow the functional characterization of an unprecedented number of sequence variants in both gene regulatory regions and protein coding sequences. This has enabled the study of nearly complete combinatorial libraries of mutational variants and revealed the widespread influence of higher-order genetic interactions that arise when multiple mutations are combined. However, the lack of appropriate tools for exploratory analysis of this high-dimensional data limits our overall understanding of the main qualitative properties of complex genotype-phenotype maps. To fill this gap, we have developed gpmap-tools (https://github.com/cmarti/gpmap-tools), a python library that integrates Gaussian process models for inference, phenotypic imputation, and error estimation from incomplete and noisy MAVE data and collections of natural sequences, together with methods for summarizing patterns of higher-order epistasis and non-linear dimensionality reduction techniques that allow visualization of genotype-phenotype maps containing up to millions of genotypes. Here, we used gpmap-tools to study the genotype-phenotype map of the Shine-Dalgarno sequence, a motif that modulates binding of the 16S rRNA to the 5' untranslated region (UTR) of mRNAs through base pair complementarity during translation initiation in prokaryotes. We inferred full combinatorial landscapes containing 262,144 different sequences from the sequences of 5,311 5'UTRs in the E. coli genome and from experimental MAVE data. Visualizations of the inferred landscapes were largely consistent with each other, and unveiled a simple molecular mechanism underlying the highly epistatic genotype-phenotype map of the Shine-Dalgarno sequence.

Gradients of Cell Recognition Molecules Wire Visuomotor Transformation

Converting sensory information into motor commands is fundamental to most of our actions 1,2 . In Drosophila , visuomotor transformations are mediated by Visual Projection Neurons (VPNs) 3,4 . These neurons encode object location and motion to drive directional behaviors through a synaptic gradient mechanism 5 . However, the molecular origins of such graded connectivity remain unknown. We addressed this question in a VPN cell type called LPLC2 6 , which integrates looming motion and transforms it into an escape response through two separate dorsoventral synaptic gradients at its inputs and outputs. We identified two corresponding dorsoventral expression gradients of cell recognition molecules within the LPLC2 population that regulate this synaptic connectivity. Dpr13 determines synaptic outputs of LPLC2 axons by interacting with its binding partner, DIP-ε, expressed in the Giant Fiber - a neuron that mediates escape 7 . Similarly, Beat-VI regulates synaptic inputs onto LPLC2 dendrites by interacting with Side-II expressed in upstream motion-detecting neurons. Behavioral, physiological, and molecular experiments demonstrate that these coordinated molecular gradients regulate synaptic connectivity, enabling the accurate transformation of visual features into motor commands. As continuous variation in gene expression within a neuronal type is also observed in the mammalian brain 8 , graded expression of cell recognition molecules may represent a common mechanism underlying synaptic specificity.

Chemotherapeutic 6-thio-2'-deoxyguanosine selectively targets and inhibits telomerase by inducing a non-productive telomere-bound telomerase complex

Most cancers upregulate the telomere lengthening enzyme telomerase to achieve unlimited cell division. How chemotherapeutic nucleoside 6-thio-2'-deoxyguanosine (6-thio-dG) targets telomerase to inhibit telomere maintenance in cancer cells and tumors was unclear. Here, we demonstrate that telomerase insertion of 6-thio-dGTP prevents synthesis of additional telomeric repeats but does not disrupt telomerase binding to telomeres. Specifically, 6-thio-dG inhibits telomere extension after telomerase translocates along its product DNA to reposition the template, inducing a non-productive complex rather than enzyme dissociation. Furthermore, we provide direct evidence that 6-thio-dG treatment inhibits telomere synthesis by telomerase in cancer cells. In agreement, telomerase-expressing cancer cells harboring critically short telomeres are more sensitive to 6-thio-dG and show a greater induction of telomere losses compared to cancer cells with long telomere reserves. Our studies reveal that telomere length and telomerase status determine 6-thio-dG sensitivity and uncover the molecular mechanism by which 6-thio-dG selectively inhibits telomerase synthesis of telomeric DNA.

Spaces and sequences in the hippocampus: a homological perspective

Topological techniques have become a popular tool for studying information flows in neural networks. In particular, simplicial homology theory is used to analyze how cognitive representations of space emerge from large conglomerates of independent neuronal contributions. Meanwhile, a growing number of studies suggest that many cognitive functions are sustained by serial patterns of activity. Here, we investigate stashes of such patterns using path homology theory-an impartial, universal approach that does not require a priori assumptions about the sequences' nature, functionality, underlying mechanisms, or other contexts. We focus on the hippocampus-a key enabler of learning and memory in mammalian brains-and quantify the ordinal arrangement of its activity similarly to how its topology has previously been studied in terms of simplicial homologies. The results reveal that the vast majority of sequences produced during spatial navigation are structurally equivalent to one another. Only a few classes of distinct sequences form an ordinal schema of serial activity that remains stable as the pool of sequences consolidates. Importantly, the structure of both maps is upheld by combinations of short sequences, suggesting that brief activity motifs dominate physiological computations. This ordinal organization emerges and stabilizes on timescales characteristic of spatial learning, displaying similar dynamics. Yet, the ordinal maps generally do not reflect topological affinities-spatial and sequential analyses address qualitatively different aspects of spike flows, representing two complementary formats of information processing.

Significance statement

This study employs path homology theory to examine serial patterns of neuronal activity in the hippocampus, a critical region for learning and memory. While the traditional, simplicial homology approaches used to model cognitive maps, path homology provides a universal framework for analyzing the ordinal arrangement of neuronal sequences without presupposing their nature or function. The findings reveal that a limited number of distinct sequence classes, supported by combinations of short activity motifs, form a stable ordinal schema over timescales corresponding to periods of spatial learning. Notably, the ordinal maps derived from these sequences do not capture topological affinities, highlighting that spatial and sequential analyses address distinct but complementary dimensions of neural information processing.

Social Risk Coding by Amygdala Activity and Connectivity with the Dorsal Anterior Cingulate Cortex

Risk is a fundamental factor affecting individual and social economic decisions, but its neural correlates are largely unexplored in the social domain. The amygdala, together with the dorsal anterior cingulate cortex (dACC), is thought to play a central role in risk-taking. Here, we investigated in human volunteers (n = 20; 11 females) how risk (defined as the variance of reward probability distributions) in a social situation affects decisions and concomitant neural activity as measured with fMRI. We found separate variance-risk signals for social and nonsocial outcomes in the amygdala. Specifically, amygdala activity increased parametrically with social reward variance of presented choice options and on separate trials with nonsocial reward variance. Behaviorally, 75% of participants were averse to social risk as estimated in a Becker-DeGroot-Marschak auction-like procedure. The stronger this aversion, the more negative the coupling between risk-related amygdala regions and dACC. This negative relation was significant for social risk attitude but not for the attitude toward variance-risk in juice outcomes. Our results indicate that the amygdala and its coupling with dACC process objective and subjectively evaluated social risk. Moreover, while social risk can be captured with a framework originally established by finance theory for nonsocial risk, the amygdala appears to process social risk largely separately from nonsocial risk.

Ancient biases in phenotype production drove the functional evolution of a protein family

Biological systems may be biased in the phenotypes they can access by mutation1-7, but the extent of these biases and their causal role in the evolution of extant phenotypic diversity remains unclear. There are three major challenges: it is difficult to isolate the effect of bias in the genotype-phenotype (GP) map from that of natural selection in producing natural diversity6,8-11, the universe of possible genotypes and phenotypes is so vast and complex that a direct characterization has been impossible, and most extant phenotypes evolved long ago in species whose GP maps cannot be recovered. Here we develop exhaustive multi-phenotype deep mutational scanning to experimentally characterize the complete GP maps of two reconstructed ancestral steroid receptor proteins, which existed during an ancient phylogenetic interval when a new phenotype-specific binding of a new DNA response element-evolved12. We measured all possible DNA specificity phenotypes encoded by all possible amino acid combinations at sites in the protein's DNA binding interface. We found that the ancestral GP maps are structured by strong global bias-unequal propensity to encode the various phenotypes-and extreme heterogeneity in the phenotypes accessible around each genotype, which strongly affect evolution on both long and short timescales. Distinct biases in the two ancestral maps steered evolution toward the lineage-specific functional phenotypes that evolved during history. Our findings establish that ancient biases in the GP relationship were causal factors in the evolutionary process that produced the present-day patterns of phenotypic conservation and diversity in this protein family.

Dissecting the functional heterogeneity of glutamatergic synapses with high-throughput optical physiology

Fluorescent reporters for glutamate release and postsynaptic Ca2+ signaling are essential tools for quantifying synapse functional heterogeneity across neurons and circuits. However, leveraging these probes for neuroscience requires scalable experimental frameworks. Here, we devised a high-throughput approach to efficiently collect and analyze hundreds of optical recordings of glutamate release activity at presynaptic boutons in cultured rat hippocampal neurons. Boutons exhibited remarkable functional heterogeneity and could be separated into multiple functional classes based on their iGluSnFR3 responses to single action potentials, paired stimuli, and synaptic parameters derived from mean-variance analysis. Finally, we developed a novel all-optical assay of pre- and postsynaptic glutamatergic synapse function. We deployed iGluSnFR3 with a red-shifted, postsynaptically-targeted Ca2+ sensor, enabling direct imaging and analysis of NMDA receptor-mediated synaptic transmission at large numbers of dendritic spines. This work enables direct observation of the flow of information at single synapses and should speed detailed investigations of synaptic functional heterogeneity.

P23H rhodopsin aggregation in the ER causes synaptic protein imbalance in rod photoreceptors

Rod photoreceptor neurons in the retina detect scotopic light through the visual pigment rhodopsin (Rho) in their outer segments (OS). Efficient Rho trafficking to the OS through the inner rod compartments is critical for long-term rod health. Given the importance of protein trafficking to the OS, less is known about the trafficking of rod synaptic proteins. Furthermore, the subcellular impact of Rho mislocalization on rod synapses (i.e., "spherules") has not been investigated. In this study we used super-resolution and electron microscopies, along with proteomics, to perform a subcellular analysis of Rho synaptic mislocalization in P23H-Rho-RFP mutant mice. We discovered that mutant P23H-Rho-RFP protein mislocalized in distinct ER aggregations within the spherule cytoplasm, which we confirmed with AAV overexpression. Additionally, we found synaptic protein abundance differences in P23H-Rho-RFP mice. By comparison, Rho mislocalized along the spherule plasma membrane in WT and rd10 mutant rods, in which there was no synaptic protein disruption. Throughout the study, we also identified a network of ER membranes within WT rod presynaptic spherules. Together, our findings indicate that photoreceptor synaptic proteins are sensitive to ER dysregulation.

tet2 and tet3 regulate cell fate specification and differentiation events during retinal development

Tet enzymes are epigenetic modifiers that impact gene expression via 5mC to 5hmC oxidation. Previous work demonstrated the requirement for Tet and 5hmC during zebrafish retinogenesis. tet2 -/- ;tet3 -/- mutants possessed defects in the formation of differentiated retinal neurons, but the mechanisms underlying these defects are unknown. Here, we leveraged scRNAseq technologies to better understand cell type-specific deficits and molecular signatures underlying the tet2 -/- ;tet3 -/- retinal phenotype. Our results identified defects in the tet2 -/- ;tet3 -/- retinae that included delayed specification of several retinal cell types, reduced maturity across late-stage cones, expansions of immature subpopulations of horizontal and bipolar cells, and altered biases of bipolar cell subtype fates at late differentiation stages. Together, these data highlight the critical role that tet2 and tet3 play as regulators of cell fate specification and terminal differentiation events during retinal development.

Human heart assembloids with autologous tissue-resident macrophages recreate physiological immuno-cardiac interactions

Interactions between the developing heart and the embryonic immune system are essential for proper cardiac development and maintaining homeostasis, with disruptions linked to various diseases. While human pluripotent stem cell (hPSC)-derived organoids are valuable models for studying human organ function, they often lack critical tissue-resident immune cells. Here, we introduce an advanced human heart assembloid model, termed hHMA (human heart-macrophage assembloid), which fully integrates autologous cardiac tissue- resident macrophages (MPs) with pre-existing human heart organoids (hHOs). Through multi-omic analyses, we confirmed that these MPs are phenotypically similar to embryonic cardiac tissue-resident MPs and remain viable in the assembloids over time. The inclusion of MPs significantly impacts hHMA development, influencing cardiac cellular composition, boosting cellular communication, remodeling the extracellular matrix, promoting ventricular morphogenesis, and enhancing sarcomeric maturation. Our findings indicate that MPs contribute to homeostasis via efferocytosis, integrate into the cardiomyocyte electrical system, and support catabolic metabolism. To demonstrate the versatility of this model, we developed a platform to study cardiac arrhythmias by chronic exposure to pro-inflammatory factors linked to arrhythmogenesis in clinical settings, successfully replicating key features of inflammasome-mediated atrial fibrillation. Overall, this work introduces a robust platform for examining the role of immune cells in cardiac development, disease mechanisms, and drug discovery, bridging the gap between in vitro models and human physiology. These findings offer insights into cardiogenesis and inflammation-driven heart disease, positioning the hHMA system as an invaluable tool for future cardiovascular research and therapeutic development.

Spatiotemporal Mapping of Auditory Onsets during Speech Production

The human auditory cortex is organized according to the timing and spectral characteristics of speech sounds during speech perception. During listening, the posterior superior temporal gyrus is organized according to onset responses, which segment acoustic boundaries in speech, and sustained responses, which further process phonological content. When we speak, the auditory system is actively processing the sound of our own voice to detect and correct speech errors in real time. This manifests in neural recordings as suppression of auditory responses during speech production compared with perception, but whether this differentially affects the onset and sustained temporal profiles is not known. Here, we investigated this question using intracranial EEG recorded from seventeen pediatric, adolescent, and adult patients with medication-resistant epilepsy while they performed a reading/listening task. We identified onset and sustained responses to speech in the bilateral auditory cortex and observed a selective suppression of onset responses during speech production. We conclude that onset responses provide a temporal landmark during speech perception that is redundant with forward prediction during speech production and are therefore suppressed. Phonological feature tuning in these "onset suppression" electrodes remained stable between perception and production. Notably, auditory onset responses and phonological feature tuning were present in the posterior insula during both speech perception and production, suggesting an anatomically and functionally separate auditory processing zone that we believe to be involved in multisensory integration during speech perception and feedback control.

Identification of TAP2 protein variants resistant to inhibition by the HSV1 ICP47 protein

Herpes Simplex Virus 1 evades the host immune system by expressing a protein, ICP47, that binds to and inhibits the heterodimeric Transporter Associated with Antigen Processing (TAP). We screened a library of 1786 variants in TAP2, one of the components of the TAP heterodimer, and identified 39 variants that were resistant to inhibition by ICP47. Of these 39 variants, five were individually tested, and three (T257I, S274H, and T244R) were confirmed to be significantly resistant to inhibition by ICP47. This resistance to inhibition did not extend to the Epstein Barr Virus BNLF2a protein, another viral factor known to inhibit antigen presentation by targeting TAP. These three residues localize close to the binding site of ICP47, on the 3D structure of TAP, but only Ser274 is spatially close to the antigenic peptide binding site of TAP. These results functionally resolve the TAP2 residues required for peptide binding from those required for ICP47 binding and identify TAP2 residues whose targeting with small molecule inhibitors could effectively prevent Herpes virus downregulation of antigen processing.

Oligodendrocytes use postsynaptic proteins to coordinate myelin formation on axons of distinct neurotransmitter classes

Axon myelination can tune neuronal circuits through placement and modulation of different patterns of myelin sheaths on distinct types of axons. How myelin formation is coordinated on distinct axon classes remains largely unknown. Recent work indicates neuronal activity and vesicle release promote myelin formation, and myelin-producing oligodendrocytes express canonical postsynaptic factors that potentially facilitate oligodendrocyte-axon interaction for myelin ensheathment. Here, we examined whether the inhibitory postsynaptic scaffold protein Gephyrin (Gphn) mediates selective myelination of specific axon classes in the larval zebrafish. Consistent with this possibility, Gphn was enriched in myelin on GABAergic and glycinergic axons. Strikingly, in gphnb deficient larvae, myelin sheaths were longer specifically on GABAergic axons, and the frequency of myelin placement shifted toward glutamatergic axons at the expense of GABAergic axons. Collectively, our results indicate that oligodendrocytes use postsynaptic machinery to coordinate myelin formation in an axon identity-dependent manner.

CRISPR screens in iPSC-derived neurons reveal principles of tau proteostasis

Aggregation of the protein tau defines tauopathies, which include Alzheimer's disease and frontotemporal dementia. Specific neuronal subtypes are selectively vulnerable to tau aggregation and subsequent dysfunction and death, but the underlying mechanisms are unknown. To systematically uncover the cellular factors controlling the accumulation of tau aggregates in human neurons, we conducted a genome-wide CRISPRi-based modifier screen in iPSC-derived neurons. The screen uncovered expected pathways, including autophagy, but also unexpected pathways, including UFMylation and GPI anchor synthesis. We discover that the E3 ubiquitin ligase CUL5SOCS4 is a potent modifier of tau levels in human neurons, ubiquitinates tau, and is a correlated with vulnerability to tauopathies in mouse and human. Disruption of mitochondrial function promotes proteasomal misprocessing of tau, which generates tau proteolytic fragments like those in disease and changes tau aggregation in vitro. These results reveal new principles of tau proteostasis in human neurons and pinpoint potential therapeutic targets for tauopathies.

Neural basis of concurrent deliberation toward a choice and degree of confidence

Decision confidence plays a key role in flexible behavior and (meta)cognition, but its underlying neural mechanisms remain elusive. To uncover the latent dynamics of confidence formation at the level of population activity, we designed a decision task for nonhuman primates that measures choice, reaction time, and confidence with a single eye movement on every trial. Monkey behavior was well fit by a bounded accumulator model instantiating parallel processing of evidence, rejecting a serial model in which the choice is resolved first followed by post-decision accumulation for confidence. Neurons in area LIP reflected concurrent accumulation, exhibiting covariation of choice and confidence signals across the population, and within-trial dynamics consistent with parallel updating at near-zero time lag. The results demonstrate that monkeys can process a single stream of evidence in service of two computational goals simultaneously-a categorical decision and associated level of confidence-and illuminate a candidate neural substrate for this ability.

Machine learning-optimized targeted detection of alternative splicing

RNA-sequencing (RNA-seq) is widely adopted for transcriptome analysis but has inherent biases which hinder the comprehensive detection and quantification of alternative splicing. To address this, we present an efficient targeted RNA-seq method that greatly enriches for splicing-informative junction-spanning reads. Local Splicing Variation sequencing (LSV-seq) utilizes multiplexed reverse transcription from highly scalable pools of primers anchored near splicing events of interest. Primers are designed using Optimal Prime, a novel machine learning algorithm trained on the performance of thousands of primer sequences. In experimental benchmarks, LSV-seq achieves high on-target capture rates and concordance with RNA-seq, while requiring significantly lower sequencing depth. Leveraging deep learning splicing code predictions, we used LSV-seq to target events with low coverage in GTEx RNA-seq data and newly discover hundreds of tissue-specific splicing events. Our results demonstrate the ability of LSV-seq to quantify splicing of events of interest at high-throughput and with exceptional sensitivity.

Heterogeneity in Slow Synaptic Transmission Diversifies Purkinje Cell Timing

The cerebellum plays an important role in diverse brain functions, ranging from motor learning to cognition. Recent studies have suggested that molecular and cellular heterogeneity within cerebellar lobules contributes to functional differences across the cerebellum. However, the specific relationship between molecular and cellular heterogeneity and diverse functional outputs of different regions of the cerebellum remains unclear. Here, we describe a previously unappreciated form of synaptic heterogeneity at parallel fiber synapses to Purkinje cells in the mouse cerebellum (both sexes). In contrast to uniform fast synaptic transmission, we found that the properties of slow synaptic transmission varied by up to threefold across different lobules of the mouse cerebellum, resulting in surprising heterogeneity. Depending on the location of a Purkinje cell, the time of peak of slow synaptic currents varied by hundreds of milliseconds. The duration and decay time of these currents also spanned hundreds of milliseconds, based on lobule. We found that, as a consequence of the heterogeneous synaptic dynamics, the same brief input stimulus was transformed into prolonged firing patterns over a range of timescales that depended on Purkinje cell location.

HI-FISH: WHOLE BRAIN IN SITU MAPPING OF NEURONAL ACTIVATION IN DROSOPHILA DURING SOCIAL BEHAVIORS AND OPTOGENETIC STIMULATION

Monitoring neuronal activity at single-cell resolution in freely moving Drosophila engaged in social behaviors is challenging because of their small size and lack of transparency. Extant methods, such as Flyception, are highly invasive. Whole-brain calcium imaging in head-fixed, walking flies is feasible but the animals cannot perform the consummatory phases of social behaviors like aggression or mating under these conditions. This has left open the fundamental question of whether neurons identified as functionally important for such behaviors using loss- or gain-of-function screens are actually active during the natural performance of such behaviors, and if so during which phase(s). Here we perform brain-wide mapping of active cells expressing the Immediate Early Gene hr38 using a high-sensitivity/low background FISH amplification method called HCR-3.0. Using double-labeling for hr38 mRNA and for GFP, we describe the activity of several classes of aggression-promoting neurons during courtship and aggression, including P1a cells, an intensively studied population of male-specific interneurons. Using HI-FISH in combination with optogenetic activation of aggression-promoting neurons (opto-HI-FISH) we identify candidate downstream functional targets of these cells in a brain-wide, unbiased manner. Finally we compare the activity of P1a neurons during sequential performance of courtship and aggression, using intronic vs. exonic hr38 probes to differentiate newly synthesized nuclear transcripts from cytoplasmic transcripts synthesized at an earlier time. These data provide evidence suggesting that different subsets of P1a neurons may be active during courtship vs. aggression. HI-FISH and associated methods may help to fill an important lacuna in the armamentarium of tools for neural circuit analysis in Drosophila.

Integrative spatiotemporal modeling of biomolecular processes: application to the assembly of the Nuclear Pore Complex

Dynamic processes involving biomolecules are essential for the function of the cell. Here, we introduce an integrative method for computing models of these processes based on multiple heterogeneous sources of information, including time-resolved experimental data and physical models of dynamic processes. We first compute integrative structure models at fixed time points and then optimally select and connect these snapshots into a series of trajectories that optimize the likelihood of both the snapshots and transitions between them. The method is demonstrated by application to the assembly process of the human Nuclear Pore Complex in the context of the reforming nuclear envelope during mitotic cell division, based on live-cell correlated electron tomography, bulk fluorescence correlation spectroscopy-calibrated quantitative live imaging, and a structural model of the fully-assembled Nuclear Pore Complex. Modeling of the assembly process improves the model precision over static integrative structure modeling alone. The method is applicable to a wide range of time-dependent systems in cell biology, and is available to the broader scientific community through an implementation in the open source Integrative Modeling Platform software.

β3 accelerates microtubule plus end maturation through a divergent lateral interface

β-tubulin isotypes exhibit similar sequences but different activities, suggesting that limited sequence divergence is functionally important. We investigated this hypothesis for TUBB3/β3, a β-tubulin linked to aggressive cancers and chemoresistance in humans. We created mutant yeast strains with β-tubulin alleles that mimic variant residues in β3 and find that residues at the lateral interface are sufficient to alter microtubule dynamics and response to microtubule targeting agents. In HeLa cells, β3 overexpression decreases the lifetime of microtubule growth, and this requires residues at the lateral interface. These microtubules exhibit a shorter region of EB binding at the plus end, suggesting faster lattice maturation, and resist stabilization by paclitaxel. Resistance requires the H1-S2 and H2-S3 regions at the lateral interface of β3. Our results identify the mechanistic origins of the unique activity of β3 tubulin and suggest that tubulin isotype expression may tune the rate of lattice maturation at growing microtubule plus ends in cells.

Suppressing phagocyte activation by overexpressing the phosphatidylserine lipase ABHD12 preserves sarmopathic nerves

Programmed axon degeneration (AxD) is a key feature of many neurodegenerative diseases. In healthy axons, the axon survival factor NMNAT2 inhibits SARM1, the central executioner of AxD, preventing it from initiating the rapid local NAD+ depletion and metabolic catastrophe that precipitates axon destruction. Because these components of the AxD pathway act within neurons, it was also assumed that the timetable of AxD was set strictly by a cell-intrinsic mechanism independent of neuron-extrinsic processes later activated by axon fragmentation. However, using a rare human disease model of neuropathy caused by hypomorphic NMNAT2 mutations and chronic SARM1 activation (sarmopathy), we demonstrated that neuronal SARM1 can initiate macrophage-mediated axon elimination long before stressed-but-viable axons would otherwise succumb to cell-intrinsic metabolic failure. Investigating potential SARM1-dependent signals that mediate macrophage recognition and/or engulfment of stressed-but-viable axons, we found that chronic SARM1 activation triggers axonal blebbing and dysregulation of phosphatidylserine (PS), a potent phagocyte immunomodulatory molecule. Neuronal expression of the phosphatidylserine lipase ABDH12 suppresses nerve macrophage activation, preserves motor axon integrity, and rescues motor function in this chronic sarmopathy model. We conclude that PS dysregulation is an early SARM1-dependent axonal stress signal, and that blockade of phagocytic recognition and engulfment of stressed-but-viable axons could be an attractive therapeutic target for management of neurological disorders involving SARM1 activation.

Atypical Protein Kinase C Promotes its own Asymmetric Localisation by Phosphorylating Cdc42 in the C. elegans zygote

Atypical protein kinase C (aPKC) is a major regulator of cell polarity. Acting in conjunction with Par6, Par3 and the small GTPase Cdc42, aPKC becomes asymmetrically localised and drives the polarisation of cells. aPKC activity is crucial for its own asymmetric localisation, suggesting a hitherto unknown feedback mechanism contributing to polarisation. Here we show in the C. elegans zygote that the feedback relies on aPKC phosphorylation of Cdc42 at serine 71. The turnover of CDC-42 phosphorylation ensures optimal aPKC asymmetry and activity throughout polarisation by tuning Par6/aPKC association with Par3 and Cdc42. Moreover, turnover of Cdc42 phosphorylation regulates actomyosin cortex dynamics that are known to drive aPKC asymmetry. Given the widespread role of aPKC and Cdc42 in cell polarity, this form of self-regulation of aPKC may be vital for the robust control of polarisation in many cell types.

The Mlh1-Pms1 endonuclease uses ATP to preserve DNA discontinuities as strand discrimination signals to facilitate mismatch repair

In eukaryotic post-replicative mismatch repair, MutS homologs (MSH) detect mismatches and recruit MLH complexes to nick the newly replicated DNA strand upon activation by the replication processivity clamp, PCNA. This incision enables mismatch removal and DNA repair. Biasing MLH endonuclease activity to the newly replicated DNA strand is crucial for repair. In reconstituted in vitro assays, PCNA is loaded at pre-existing discontinuities and orients the major MLH endonuclease Mlh1-Pms1/MLH1-PMS2 (yeast/human) to nick the discontinuous strand. In vivo, newly replicated DNA transiently contains discontinuities which are critical for efficient mismatch repair. How these discontinuities are preserved as strand discrimination signals during the window of time where mismatch repair occurs is unknown. Here, we demonstrate that yeast Mlh1-Pms1 uses ATP binding to recognize DNA discontinuities. This complex does not efficiently interact with PCNA, which partially suppresses ATPase activity, and prevents dissociation from the discontinuity. These data suggest that in addition to initiating mismatch repair by nicking newly replicated DNA, Mlh1-Pms1 protects strand discrimination signals, aiding in maintaining its own strand discrimination signposts. Our findings also highlight the significance of Mlh1-Pms1's ATPase activity for inducing DNA dissociation, as mutant proteins deficient in this function become immobilized on DNA post-incision, explaining in vivo phenotypes.

Cholesterol inhibits assembly and activation of the EphA2 receptor

The receptor tyrosine kinase EphA2 drives cancer malignancy by facilitating metastasis. EphA2 can be found in different self-assembly states: as a monomer, dimer, and oligomer. However, our understanding remains limited regarding which EphA2 state is responsible for driving pro-metastatic signaling. To address this limitation, we have developed SiMPull-POP, a single-molecule method for accurate quantification of membrane protein self-assembly. Our experiments revealed that a reduction of plasma membrane cholesterol strongly promoted EphA2 self-assembly. Indeed, low cholesterol caused a similar effect to the EphA2 ligand ephrinA1-Fc. These results indicate that cholesterol inhibits EphA2 assembly. Phosphorylation studies in different cell lines revealed that low cholesterol increased phospho-serine levels, the signature of oncogenic signaling. Investigation of the mechanism that cholesterol uses to inhibit the assembly and activity of EphA2 indicate an in-trans effect, where EphA2 is phosphorylated by protein kinase A downstream of beta-adrenergic receptor activity, which cholesterol also inhibits. Our study not only provides new mechanistic insights on EphA2 oncogenic function, but also suggests that cholesterol acts as a molecular safeguard mechanism that prevents uncontrolled self-assembly and activation of EphA2.

Pattern completion and disruption characterize contextual modulation in the visual cortex

Vision is fundamentally context-dependent, with neuronal responses influenced not just by local features but also by surrounding contextual information. In the visual cortex, studies using simple grating stimuli indicate that congruent stimuli - where the center and surround share the same orientation - are more inhibitory than when orientations are orthogonal, potentially serving redundancy reduction and predictive coding. Understanding these center-surround interactions in relation to natural image statistics is challenging due to the high dimensionality of the stimulus space, yet crucial for deciphering the neuronal code of real-world sensory processing. Utilizing large-scale recordings from mouse V1, we trained convolutional neural networks (CNNs) to predict and synthesize surround patterns that either optimally suppressed or enhanced responses to center stimuli, confirmed by in vivo experiments. Contrary to the notion that congruent stimuli are suppressive, we found that surrounds that completed patterns based on natural image statistics were facilitatory, while disruptive surrounds were suppressive. Applying our CNN image synthesis method in macaque V1, we discovered that pattern completion within the near surround occurred more frequently with excitatory than with inhibitory surrounds, suggesting that our results in mice are conserved in macaques. Further, experiments and model analyses confirmed previous studies reporting the opposite effect with grating stimuli in both species. Using the MICrONS functional connectomics dataset, we observed that neurons with similar feature selectivity formed excitatory connections regardless of their receptive field overlap, aligning with the pattern completion phenomenon observed for excitatory surrounds. Finally, our empirical results emerged in a normative model of perception implementing Bayesian inference, where neuronal responses are modulated by prior knowledge of natural scene statistics. In summary, our findings identify a novel relationship between contextual information and natural scene statistics and provide evidence for a role of contextual modulation in hierarchical inference.

Balancing the Senses: Electrophysiological Responses Reveal the Interplay between Somatosensory and Visual Processing During Body-Related Multisensory Conflict

In the study of bodily awareness, the predictive coding theory has revealed that our brain continuously modulates sensory experiences to integrate them into a unitary body representation. Indeed, during multisensory illusions (e.g., the rubber hand illusion, RHI), the synchronous stroking of the participant's concealed hand and a fake visible one creates a visuotactile conflict, generating a prediction error. Within the predictive coding framework, through sensory processing modulation, prediction errors are solved, inducing participants to feel as if touches originated from the fake hand, thus ascribing the fake hand to their own body. Here, we aimed to address sensory processing modulation under multisensory conflict, by disentangling somatosensory and visual stimuli processing that are intrinsically associated during the illusion induction. To this aim, we designed two EEG experiments, in which somatosensory- (SEPs; Experiment 1; N = 18; F = 10) and visual-evoked potentials (VEPs; Experiment 2; N = 18; F = 9) were recorded in human males and females following the RHI. Our results show that, in both experiments, ERP amplitude is significantly modulated in the illusion as compared with both control and baseline conditions, with a modality-dependent diametrical pattern showing decreased SEP amplitude and increased VEP amplitude. Importantly, both somatosensory and visual modulations occur in long-latency time windows previously associated with tactile and visual awareness, thus explaining the illusion of perceiving touch at the sight location. In conclusion, we describe a diametrical modulation of somatosensory and visual processing as the neural mechanism that allows maintaining a stable body representation, by restoring visuotactile congruency under the occurrence of multisensory conflicts.

E-cadherin tunes tissue mechanical behavior before and during morphogenetic tissue flows

Adhesion between epithelial cells enables the remarkable mechanical behavior of epithelial tissues during morphogenesis. However, it remains unclear how cell-cell adhesion influences mechanics in static as well as in dynamically flowing epithelial tissues. Here, we systematically modulate E-cadherin-mediated adhesion in the Drosophila embryo and study the effects on the mechanical behavior of the germband epithelium before and during dramatic tissue remodeling and flow associated with body axis elongation. Before axis elongation, we find that increasing E-cadherin levels produces tissue comprising more elongated cells and predicted to be more fluid-like, providing reduced resistance to tissue flow. During axis elongation, we find that the dominant effect of E-cadherin is tuning the speed at which cells proceed through rearrangement events, revealing potential roles for E-cadherin in generating friction between cells. Before and during axis elongation, E-cadherin levels influence patterns of actomyosin-dependent forces, supporting the notion that E-cadherin tunes tissue mechanics in part through effects on actomyosin. Taken together, these findings reveal dual-and sometimes opposing-roles for E-cadherin-mediated adhesion in controlling tissue structure and dynamics in vivo that result in unexpected relationships between adhesion and flow.

Molecular differences between neonatal and adult stria vascularis from organotypic explants and transcriptomics

Summary

The stria vascularis (SV), part of the blood-labyrinth barrier, is an essential component of the inner ear that regulates the ionic environment required for hearing. SV degeneration disrupts cochlear homeostasis, leading to irreversible hearing loss, yet a comprehensive understanding of the SV, and consequently therapeutic availability for SV degeneration, is lacking. We developed a whole-tissue explant model from neonatal and adult mice to create a robust platform for SV research. We validated our model by demonstrating that the proliferative behaviour of the SV in vitro mimics SV in vivo, providing a representative model and advancing high-throughput SV research. We also provided evidence for pharmacological intervention in our system by investigating the role of Wnt/β-catenin signaling in SV proliferation. Finally, we performed single-cell RNA sequencing from in vivo neonatal and adult mouse SV and revealed key genes and pathways that may play a role in SV proliferation and maintenance. Together, our results contribute new insights into investigating biological solutions for SV-associated hearing loss.

Significance

Hearing loss impairs our ability to communicate with people and interact with our environment. This can lead to social isolation, depression, cognitive deficits, and dementia. Inner ear degeneration is a primary cause of hearing loss, and our study provides an in depth look at one of the major sites of inner ear degeneration: the stria vascularis. The stria vascularis and associated blood-labyrinth barrier maintain the functional integrity of the auditory system, yet it is relatively understudied. By developing a new in vitro model for the young and adult stria vascularis and using single cell RNA sequencing, our study provides a novel approach to studying this tissue, contributing new insights and widespread implications for auditory neuroscience and regenerative medicine.

Highlights

- We established an organotypic explant system of the neonatal and adult stria vascularis with an intact blood-labyrinth barrier. - Proliferation of the stria vascularis decreases with age in vitro , modelling its proliferative behaviour in vivo . - Pharmacological studies using our in vitro SV model open possibilities for testing injury paradigms and therapeutic interventions. - Inhibition of Wnt signalling decreases proliferation in neonatal stria vascularis.- We identified key genes and transcription factors unique to developing and mature SV cell types using single cell RNA sequencing.

Serotonin acts through multiple cellular targets during an olfactory critical period

Serotonin (5-HT) is known to modulate early development during critical periods when experience drives heightened levels of plasticity in neurons. Here, we take advantage of the genetically tractable olfactory system of Drosophila to investigate how 5-HT modulates critical period plasticity in the CO2 sensing circuit of fruit flies. Our study reveals that 5HT modulation of multiple neuronal targets is necessary for experience-dependent structural changes in an odor processing circuit. The olfactory CPP is known to involve local inhibitory networks and consistent with this we found that knocking down 5-HT7 receptors in a subset of GABAergic local interneurons was sufficient to block CPP, as was knocking down GABA receptors expressed by olfactory sensory neurons (OSNs). Additionally, direct modulation of OSNs via 5-HT2B expression in the cognate OSNs sensing CO2 is also essential for CPP. Furthermore, 5-HT1B expression by serotonergic neurons in the olfactory system is also required during the critical period. Our study reveals that 5-HT modulation of multiple neuronal targets is necessary for experience-dependent structural changes in an odor processing circuit.

Parallel Encoding of Speech in Human Frontal and Temporal Lobes

Models of speech perception are centered around a hierarchy in which auditory representations in the thalamus propagate to primary auditory cortex, then to the lateral temporal cortex, and finally through dorsal and ventral pathways to sites in the frontal lobe. However, evidence for short latency speech responses and low-level spectrotemporal representations in frontal cortex raises the question of whether speech-evoked activity in frontal cortex strictly reflects downstream processing from lateral temporal cortex or whether there are direct parallel pathways from the thalamus or primary auditory cortex to the frontal lobe that supplement the traditional hierarchical architecture. Here, we used high-density direct cortical recordings, high-resolution diffusion tractography, and hemodynamic functional connectivity to evaluate for evidence of direct parallel inputs to frontal cortex from low-level areas. We found that neural populations in the frontal lobe show speech-evoked responses that are synchronous or occur earlier than responses in the lateral temporal cortex. These short latency frontal lobe neural populations encode spectrotemporal speech content indistinguishable from spectrotemporal encoding patterns observed in the lateral temporal lobe, suggesting parallel auditory speech representations reaching temporal and frontal cortex simultaneously. This is further supported by white matter tractography and functional connectivity patterns that connect the auditory nucleus of the thalamus (medial geniculate body) and the primary auditory cortex to the frontal lobe. Together, these results support the existence of a robust pathway of parallel inputs from low-level auditory areas to frontal lobe targets and illustrate long-range parallel architecture that works alongside the classical hierarchical speech network model.

betAS: intuitive analysis and visualization of differential alternative splicing using beta distributions

Next-generation RNA sequencing allows alternative splicing (AS) quantification with unprecedented resolution, with the relative inclusion of an alternative sequence in transcripts being commonly quantified by the proportion of reads supporting it as percent spliced-in (PSI). However, PSI values do not incorporate information about precision, proportional to the respective AS events' read coverage. Beta distributions are suitable to quantify inclusion levels of alternative sequences, using reads supporting their inclusion and exclusion as surrogates for the two distribution shape parameters. Each such beta distribution has the PSI as its mean value and is narrower when the read coverage is higher, facilitating the interpretability of its precision when plotted. We herein introduce a computational pipeline, based on beta distributions accurately modeling PSI values and their precision, to quantitatively and visually compare AS between groups of samples. Our methodology includes a differential splicing significance metric that compromises the magnitude of intergroup differences, the estimation uncertainty in individual samples, and the intragroup variability, being therefore suitable for multiple-group comparisons. To make our approach accessible and clear to both noncomputational and computational biologists, we developed betAS, an interactive web app and user-friendly R package for visual and intuitive differential splicing analysis from read count data.

A novel protein Moat prevents ectopic epithelial folding by limiting Bazooka/Par3-dependent adherens junctions

Cortical myosin contraction and cell adhesion work together to promote tissue shape changes, but how they are modulated to achieve diverse morphogenetic outcomes remains unclear. Epithelial folding occurs via apical constriction, mediated by apical accumulation of contractile myosin engaged with adherens junctions, as in Drosophila ventral furrow formation. While levels of contractile myosin correlate with apical constriction, whether levels of adherens junctions modulate apical constriction is unknown. We identified a novel Drosophila gene moat that maintains low levels of Bazooka/Par3-dependent adherens junctions and thereby restricts apical constriction to ventral furrow cells with high-level contractile myosin. In moat mutants, abnormally high levels of Bazooka/Par3-dependent adherens junctions promote ectopic apical constriction in cells with low-level contractile myosin, insufficient for apical constriction in wild type. Such ectopic apical constriction expands infolding behavior from ventral furrow to ectodermal anterior midgut, which normally forms a later circular invagination. In moat mutant ventral furrow, a perturbed apical constriction gradient delays infolding. Our results indicate that levels of adherens junctions can modulate the outcome of apical constriction, providing an additional mechanism to define morphogenetic boundaries.

Up-regulation of cholesterol synthesis by lysosomal defects requires a functional mitochondrial respiratory chain

Mitochondria and lysosomes are two organelles that carry out both signaling and metabolic roles in the cells. Recent evidence has shown that mitochondria and lysosomes are dependent on one another, as primary defects in one cause secondary defects in the other. Nevertheless, the signaling consequences of primary mitochondrial malfunction and of primary lysosomal defects are not similar, despite in both cases there are impairments of mitochondria and of lysosomes. Here, we used RNA sequencing to obtain transcriptomes from cells with primary mitochondrial or lysosomal defects, to identify what are the global cellular consequences that are associated with malfunction of mitochondria or lysosomes. We used these data to determine what are the pathways that are affected by defects in both organelles, which revealed a prominent role for the cholesterol synthesis pathway. This pathway is transcriptionally up-regulated in cellular and mouse models of lysosomal defects and is transcriptionally down-regulated in cellular and mouse models of mitochondrial defects. We identified a role for post-transcriptional regulation of the transcription factor SREBF1, a master regulator of cholesterol and lipid biosynthesis, in models of mitochondrial respiratory chain deficiency. Furthermore, the retention of Ca 2+ in the lysosomes of cells with mitochondrial respiratory chain defects contributes to the differential regulation of the cholesterol synthesis pathway in the mitochondrial and lysosomal defects tested. Finally, we verified in vivo , using models of mitochondria-associated diseases in C. elegans , that normalization of lysosomal Ca 2+ levels results in partial rescue of the developmental arrest induced by the respiratory chain deficiency.

Greater reliance on model-free learning in adolescent anorexia nervosa: An examination of dual-system reinforcement learning

Alterations in learning and decision-making systems are thought to contribute to core features of anorexia nervosa (AN), a psychiatric disorder characterized by persistent dietary restriction and weight loss. Instrumental learning theory identifies a dual-system of habit and goal-directed decision-making, linked to model-free and model-based reinforcement learning algorithms. Difficulty arbitrating between these systems, resulting in an over-reliance on one strategy over the other, has been implicated in compulsivity and extreme goal pursuit, both of which are observed in AN. Characterizing alterations in model-free and model-based systems, and their neural correlates, in AN may clarify mechanisms contributing to symptom heterogeneity (e.g., binge/purge symptoms). This study tested whether adolescents with restricting AN (AN-R; n = 36) and binge/purge AN (AN-BP; n = 20) differentially utilized model-based and model-free learning systems compared to a healthy control group (HC; n = 28) during a Markov two-step decision-making task under conditions of reward and punishment. Associations between model-free and model-based learning and resting-state functional connectivity between neural regions of interest, including orbitofrontal cortex (OFC), nucleus accumbens (NAcc), putamen, and sensory motor cortex (SMC) were examined. AN-R showed higher utilization of model-free learning compared to HC for reward, but attenuated model-free and model-based learning for punishment. In AN-R only, higher model-based learning was associated with stronger OFC-to-left NAcc functional connectivity, regions linked to goal-directed behavior. Greater utilization of model-free learning for reward in AN-R may differentiate this group, particularly during adolescence, and facilitate dietary restriction by prioritizing habitual control in rewarding contexts.

Identifying distinct neural features between the initial and corrective phases of precise reaching using AutoLFADS

Many initial movements require subsequent corrective movements, but how motor cortex transitions to make corrections and how similar the encoding is to initial movements is unclear. In our study, we explored how the brain's motor cortex signals both initial and corrective movements during a precision reaching task. We recorded a large population of neurons from two male rhesus macaques across multiple sessions to examine the neural firing rates during not only initial movements but also subsequent corrective movements. AutoLFADS, an auto-encoder-based deep-learning model, was applied to provide a clearer picture of neurons' activity on individual corrective movements across sessions. Decoding of reach velocity generalized poorly from initial to corrective submovements. Unlike initial movements, it was challenging to predict the velocity of corrective movements using traditional linear methods in a single, global neural space. We identified several locations in the neural space where corrective submovements originated after the initial reaches, signifying firing rates different than the baseline before initial movements. To improve corrective movement decoding, we demonstrate that a state-dependent decoder incorporating the population firing rates at the initiation of correction improved performance, highlighting the diverse neural features of corrective movements. In summary, we show neural differences between initial and corrective submovements and how the neural activity encodes specific combinations of velocity and position. These findings are inconsistent with assumptions that neural correlations with kinematic features are global and independent, emphasizing that traditional methods often fall short in describing these diverse neural processes for online corrective movements.

Significance Statement

We analyzed submovement neural population dynamics during precision reaching. Using an auto- encoder-based deep-learning model, AutoLFADS, we examined neural activity on a single-trial basis. Our study shows distinct neural dynamics between initial and corrective submovements. We demonstrate the existence of unique neural features within each submovement class that encode complex combinations of position and reach direction. Our study also highlights the benefit of state-specific decoding strategies, which consider the neural firing rates at the onset of any given submovement, when decoding complex motor tasks such as corrective submovements.

Does Ipsilateral Remapping Following Hand Loss Impact Motor Control of the Intact Hand?

What happens once a cortical territory becomes functionally redundant? We studied changes in brain function and behavior for the remaining hand in humans (male and female) with either a missing hand from birth (one-handers) or due to amputation. Previous studies reported that amputees, but not one-handers, show increased ipsilateral activity in the somatosensory territory of the missing hand (i.e., remapping). We used a complex finger task to explore whether this observed remapping in amputees involves recruiting more neural resources to support the intact hand to meet greater motor control demands. Using basic fMRI analysis, we found that only amputees had more ipsilateral activity when motor demand increased; however, this did not match any noticeable improvement in their behavioral task performance. More advanced multivariate fMRI analyses showed that amputees had stronger and more typical representation-relative to controls' contralateral hand representation-compared with one-handers. This suggests that in amputees, both hand areas work together more collaboratively, potentially reflecting the intact hand's efference copy. One-handers struggled to learn difficult finger configurations, but this did not translate to differences in univariate or multivariate activity relative to controls. Additional white matter analysis provided conclusive evidence that the structural connectivity between the two hand areas did not vary across groups. Together, our results suggest that enhanced activity in the missing hand territory may not reflect intact hand function. Instead, we suggest that plasticity is more restricted than generally assumed and may depend on the availability of homologous pathways acquired early in life.

Mechanisms of gas sensing by internal sensory neurons in Drosophila larvae

Internal sensory neurons monitor the chemical and physical state of the body, providing critical information to the central nervous system for maintaining homeostasis and survival. A population of larval Drosophila sensory neurons, tracheal dendrite (td) neurons, elaborate dendrites along respiratory organs and may serve as a model for elucidating the cellular and molecular basis of chemosensation by internal neurons. We find that td neurons respond to decreases in O2 levels and increases in CO2 levels. We assessed the roles of atypical soluble guanylyl cyclases (Gycs) and a gustatory receptor (Gr) in mediating these responses. We found that Gyc88E/Gyc89Db were necessary for responses to hypoxia, and that Gr28b was necessary for responses to CO2. Targeted expression of Gr28b isoform c in td neurons rescued responses to CO2 in mutant larvae and also induced ectopic sensitivity to CO2 in the td network. Gas-sensitive td neurons were activated when larvae burrowed for a prolonged duration, demonstrating a natural-like feeding condition in which td neurons are activated. Together, our work identifies two gaseous stimuli that are detected by partially overlapping subsets of internal sensory neurons, and establishes roles for Gyc88E/Gyc89Db in the detection of hypoxia, and Gr28b in the detection of CO2.

An integrated technology for quantitative wide mutational scanning of human antibody Fab libraries

Antibodies are engineerable quantities in medicine. Learning antibody molecular recognition would enable the in silico design of high affinity binders against nearly any proteinaceous surface. Yet, publicly available experiment antibody sequence-binding datasets may not contain the mutagenic, antigenic, or antibody sequence diversity necessary for deep learning approaches to capture molecular recognition. In part, this is because limited experimental platforms exist for assessing quantitative and simultaneous sequence-function relationships for multiple antibodies. Here we present MAGMA-seq, an integrated technology that combines multiple antigens and multiple antibodies and determines quantitative biophysical parameters using deep sequencing. We demonstrate MAGMA-seq on two pooled libraries comprising mutants of ten different human antibodies spanning light chain gene usage, CDR H3 length, and antigenic targets. We demonstrate the comprehensive mapping of potential antibody development pathways, sequence-binding relationships for multiple antibodies simultaneously, and identification of paratope sequence determinants for binding recognition for broadly neutralizing antibodies (bnAbs). MAGMA-seq enables rapid and scalable antibody engineering of multiple lead candidates because it can measure binding for mutants of many given parental antibodies in a single experiment.

Sound-seeking before and after hearing loss in mice

How we move our bodies affects how we perceive sound. For instance, we can explore an environment to seek out the source of a sound and we can use head movements to compensate for hearing loss. How we do this is not well understood because many auditory experiments are designed to limit head and body movements. To study the role of movement in hearing, we developed a behavioral task called sound-seeking that rewarded mice for tracking down an ongoing sound source. Over the course of learning, mice more efficiently navigated to the sound. We then asked how auditory behavior was affected by hearing loss induced by surgical removal of the malleus from the middle ear. An innate behavior, the auditory startle response, was abolished by bilateral hearing loss and unaffected by unilateral hearing loss. Similarly, performance on the sound-seeking task drastically declined after bilateral hearing loss and did not recover. In striking contrast, mice with unilateral hearing loss were only transiently impaired on sound-seeking; over a recovery period of about a week, they regained high levels of performance, increasingly reliant on a different spatial sampling strategy. Thus, even in the face of permanent unilateral damage to the peripheral auditory system, mice recover their ability to perform a naturalistic sound-seeking task. This paradigm provides an opportunity to examine how body movement enables better hearing and resilient adaptation to sensory deprivation.

Cortical Reorganization after Limb Loss: Bridging the Gap between Basic Science and Clinical Recovery

Despite the increasing incidence and prevalence of amputation across the globe, individuals with acquired limb loss continue to struggle with functional recovery and chronic pain. A more complete understanding of the motor and sensory remodeling of the peripheral and central nervous system that occurs postamputation may help advance clinical interventions to improve the quality of life for individuals with acquired limb loss. The purpose of this article is to first provide background clinical context on individuals with acquired limb loss and then to provide a comprehensive review of the known motor and sensory neural adaptations from both animal models and human clinical trials. Finally, the article bridges the gap between basic science researchers and clinicians that treat individuals with limb loss by explaining how current clinical treatments may restore function and modulate phantom limb pain using the underlying neural adaptations described above. This review should encourage the further development of novel treatments with known neurological targets to improve the recovery of individuals postamputation.Significance Statement In the United States, 1.6 million people live with limb loss; this number is expected to more than double by 2050. Improved surgical procedures enhance recovery, and new prosthetics and neural interfaces can replace missing limbs with those that communicate bidirectionally with the brain. These advances have been fairly successful, but still most patients experience persistent problems like phantom limb pain, and others discontinue prostheses instead of learning to use them daily. These problematic patient outcomes may be due in part to the lack of consensus among basic and clinical researchers regarding the plasticity mechanisms that occur in the brain after amputation injuries. Here we review results from clinical and animal model studies to bridge this clinical-basic science gap.

Learning a conserved mechanism for early neuroectoderm morphogenesis

Morphogenesis is the process whereby the body of an organism develops its target shape. The morphogen BMP is known to play a conserved role across bilaterian organisms in determining the dorsoventral (DV) axis. Yet, how BMP governs the spatio-temporal dynamics of cytoskeletal proteins driving morphogenetic flow remains an open question. Here, we use machine learning to mine a morphodynamic atlas of Drosophila development, and construct a mathematical model capable of predicting the coupled dynamics of myosin, E-cadherin, and morphogenetic flow. Mutant analysis shows that BMP sets the initial condition of this dynamical system according to the following signaling cascade: BMP establishes DV pair-rule-gene patterns that set-up an E-cadherin gradient which in turn creates a myosin gradient in the opposite direction through mechanochemical feedbacks. Using neural tube organoids, we argue that BMP, and the signaling cascade it triggers, prime the conserved dynamics of neuroectoderm morphogenesis from fly to humans.

A cognitive map for value-guided choice in ventromedial prefrontal cortex

The prefrontal cortex is crucial for economic decision-making and representing the value of options. However, how such representations facilitate flexible decisions remains unknown. We reframe economic decision-making in prefrontal cortex in line with representations of structure within the medial temporal lobe because such cognitive map representations are known to facilitate flexible behaviour. Specifically, we framed choice between different options as a navigation process in value space. Here we show that choices in a 2D value space defined by reward magnitude and probability were represented with a grid-like code, analogous to that found in spatial navigation. The grid-like code was present in ventromedial prefrontal cortex (vmPFC) local field potential theta frequency and the result replicated in an independent dataset. Neurons in vmPFC similarly contained a grid-like code, in addition to encoding the linear value of the chosen option. Importantly, both signals were modulated by theta frequency - occurring at theta troughs but on separate theta cycles. Furthermore, we found sharp-wave ripples - a key neural signature of planning and flexible behaviour - in vmPFC, which were modulated by accuracy and reward. These results demonstrate that multiple cognitive map-like computations are deployed in vmPFC during economic decision-making, suggesting a new framework for the implementation of choice in prefrontal cortex.

Mechanical positive feedback and biochemical negative feedback combine to generate complex contractile oscillations in cytokinesis

Contractile force generation by the cortical actomyosin cytoskeleton is essential for a multitude of biological processes. The actomyosin cortex behaves as an active material that drives local and large-scale shape changes via cytoskeletal remodeling in response to biochemical cues and feedback loops. Cytokinesis is the essential cell division event during which a cortical actomyosin ring generates contractile force to change cell shape and separate two daughter cells. Our recent work with active gel theory predicts that actomyosin systems under the control of a biochemical oscillator and experiencing mechanical strain will exhibit complex spatiotemporal behavior, but cytokinetic contractility was thought to be kinetically simple. To test whether active materials in vivo exhibit spatiotemporally complex kinetics, we used 4-dimensional imaging with unprecedented temporal resolution and discovered sections of the cytokinetic cortex undergo periodic phases of acceleration and deceleration. Quantification of ingression speed oscillations revealed wide ranges of oscillation period and amplitude. In the cytokinetic ring, activity of the master regulator RhoA pulsed with a timescale of approximately 20 seconds, shorter than that reported for any other biological context. Contractility oscillated with 20-second periodicity and with much longer periods. A combination of in vivo and in silico approaches to modify mechanical feedback revealed that the period of contractile oscillation is prolonged as a function of the intensity of mechanical feedback. Effective local ring ingression is characterized by slower speed oscillations, likely due to increased local stresses and therefore mechanical feedback. Fast ingression also occurs where material turnover is high, in vivo and in silico . We propose that downstream of initiation by pulsed RhoA activity, mechanical positive feedback, including but not limited to material advection, extends the timescale of contractility beyond that of biochemical input and therefore makes it robust to fluctuations in activation. Circumferential propagation of contractility likely allows sustained contractility despite cytoskeletal remodeling necessary to recover from compaction. Our work demonstrates that while biochemical feedback loops afford systems responsiveness and robustness, mechanical feedback must also be considered to describe and understand the behaviors of active materials in vivo .

A Cortico-Striatal Circuit for Sound-Triggered Prediction of Reward Timing

A crucial aspect of auditory perception is the ability to use sound cues to predict future events and to time actions accordingly. For example, distinct smartphone notification sounds reflect a call that needs to be answered within a few seconds, or a text that can be read later; the sound of an approaching vehicle signals when it is safe to cross the street. Other animals similarly use sounds to plan, time and execute behaviors such as hunting, evading predation and tending to offspring. However, the neural mechanisms that underlie sound-guided prediction of upcoming salient event timing are not well understood. To address this gap, we employed an appetitive sound-triggered reward time prediction behavior in head-fixed mice. We find that mice trained on this task reliably estimate the time from a sound cue to upcoming reward on the scale of a few seconds, as demonstrated by learning-dependent well-timed increases in reward-predictive licking. Moreover, mice showed a dramatic impairment in their ability to use sound to predict delayed reward when the auditory cortex was inactivated, demonstrating its causal involvement. To identify the neurophysiological signatures of auditory cortical reward-timing prediction, we recorded local field potentials during learning and performance of this behavior and found that the magnitude of auditory cortical responses to the sound prospectively encoded the duration of the anticipated sound-reward time interval. Next, we explored how and where these sound-triggered time interval prediction signals propagate from the auditory cortex to time and initiate consequent action. We targeted the monosynaptic projections from the auditory cortex to the posterior striatum and found that chemogenetic inactivation of these projections impairs animal's ability to predict sound-triggered delayed reward. Simultaneous neural recordings in the auditory cortex and posterior striatum during task performance revealed coordination of neural activity across these regions during the sound cue predicting the time interval to reward. Collectively, our findings identify an auditory cortical-striatal circuit supporting sound-triggered timing-prediction behaviors.

Comparative profiling of cellular gait on adhesive micropatterns defines statistical patterns of activity that underlie native and cancerous cell dynamics

Cell dynamics are powered by patterns of activity, but it is not straightforward to quantify these patterns or compare them across different environmental conditions or cell-types. Here we digitize the long-term shape fluctuations of metazoan cells grown on micropatterned fibronectin islands to define and extract statistical features of cell dynamics without the need for genetic modification or fluorescence imaging. These shape fluctuations generate single-cell morphological signals that can be decomposed into two major components: a continuous, slow-timescale meandering of morphology about an average steady-state shape; and short-lived "events" of rapid morphology change that sporadically occur throughout the timecourse. By developing statistical metrics for each of these components, we used thousands of hours of single-cell data to quantitatively define how each axis of cell dynamics was impacted by environmental conditions or cell-type. We found the size and spatial complexity of the micropattern island modulated the statistics of morphological events-lifetime, frequency, and orientation-but not its baseline shape fluctuations. Extending this approach to profile a panel of triple negative breast cancer cell-lines, we found that different cell-types could be distinguished from one another along specific and unique statistical axes of their behavior. Our results suggest that micropatterned substrates provide a generalizable method to build statistical profiles of cell dynamics to classify and compare emergent cell behaviors.