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2363 Publications

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    08/08/23 | Stimulus edges induce orientation tuning in superior colliculus.
    Liang Y, Lu R, Borges K, Ji N
    Nature Communications. 2023 Aug 08;14(1):4756. doi: 10.1038/s41467-023-40444-1

    Orientation columns exist in the primary visual cortex (V1) of cat and primates but not mouse. Intriguingly, some recent studies reported the presence of orientation and direction columns in the mouse superficial superior colliculus (sSC), while others reported a lack of columnar organization therein. Using in vivo calcium imaging of sSC in the awake mouse brain, we found that the presence of columns is highly stimulus dependent. Specifically, we observed orientation and direction columns formed by sSC neurons retinotopically mapped to the edge of grating stimuli. For both excitatory and inhibitory neurons in sSC, orientation selectivity can be induced by the edge with their preferred orientation perpendicular to the edge orientation. Furthermore, we found that this edge-induced orientation selectivity is associated with saliency encoding. These findings indicate that the tuning properties of sSC neurons are not fixed by circuit architecture but rather dependent on the spatiotemporal properties of the stimulus.

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    08/07/23 | Learning produces a hippocampal cognitive map in the form of an orthogonalized state machine.
    Weinan Sun , Johan Winnubst , Maanasa Natrajan , Chongxi Lai , Koichiro Kajikawa , Michalis Michaelos , Rachel Gattoni , Carsen Stringer , Daniel Flickinger , James E. Fitzgerald , Nelson Spruston
    bioRxiv. 2023 Aug 07:. doi: 10.1101/2023.08.03.551900

    Cognitive maps confer animals with flexible intelligence by representing spatial, temporal, and abstract relationships that can be used to shape thought, planning, and behavior. Cognitive maps have been observed in the hippocampus, but their algorithmic form and the processes by which they are learned remain obscure. Here, we employed large-scale, longitudinal two-photon calcium imaging to record activity from thousands of neurons in the CA1 region of the hippocampus while mice learned to efficiently collect rewards from two subtly different versions of linear tracks in virtual reality. The results provide a detailed view of the formation of a cognitive map in the hippocampus. Throughout learning, both the animal behavior and hippocampal neural activity progressed through multiple intermediate stages, gradually revealing improved task understanding and behavioral efficiency. The learning process led to progressive decorrelations in initially similar hippocampal neural activity within and across tracks, ultimately resulting in orthogonalized representations resembling a state machine capturing the inherent structure of the task. We show that a Hidden Markov Model (HMM) and a biologically plausible recurrent neural network trained using Hebbian learning can both capture core aspects of the learning dynamics and the orthogonalized representational structure in neural activity. In contrast, we show that gradient-based learning of sequence models such as Long Short-Term Memory networks (LSTMs) and Transformers do not naturally produce such representations. We further demonstrate that mice exhibited adaptive behavior in novel task settings, with neural activity reflecting flexible deployment of the state machine. These findings shed light on the mathematical form of cognitive maps, the learning rules that sculpt them, and the algorithms that promote adaptive behavior in animals. The work thus charts a course toward a deeper understanding of biological intelligence and offers insights toward developing more robust learning algorithms in artificial intelligence.

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    08/06/23 | Multi-day Neuron Tracking in High Density Electrophysiology Recordings using EMD
    Augustine Xiaoran Yuan , Jennifer Colonell , Anna Lebedeva , Adam Charles , Timothy Harris
    bioRxiv. 2023 Aug 06:. doi: 10.1101/2023.08.03.551724

    Accurate tracking of the same neurons across multiple days is crucial for studying changes in neuronal activity during learning and adaptation. New advances in high density extracellular electrophysiology recording probes, such as Neuropixels, provide a promising avenue to accomplish this goal. Identifying the same neurons in multiple recordings is, however, complicated by non-rigid movement of the tissue relative to the recording sites (drift) and loss of signal from some neurons. Here we propose a neuron tracking method that can identify the same cells independent of firing statistics, which are used by most existing methods. Our method is based on between-day non-rigid alignment of spike sorted clusters. We verified the same cell identify using measured visual receptive fields. This method succeeds on datasets separated from one to 47 days, with an 86% average recovery rate.

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    08/04/23 | Biomechanical origins of proprioceptor feature selectivity and topographic maps in the Drosophila leg.
    Mamiya A, Sustar A, Siwanowicz I, Qi Y, Lu T, Gurung P, Chen C, Phelps JS, Kuan AT, Pacureanu A, Lee WA, Li H, Mhatre N, Tuthill JC
    Neuron. 2023 Aug 04:. doi: 10.1016/j.neuron.2023.07.009

    Our ability to sense and move our bodies relies on proprioceptors, sensory neurons that detect mechanical forces within the body. Different subtypes of proprioceptors detect different kinematic features, such as joint position, movement, and vibration, but the mechanisms that underlie proprioceptor feature selectivity remain poorly understood. Using single-nucleus RNA sequencing (RNA-seq), we found that proprioceptor subtypes in the Drosophila leg lack differential expression of mechanosensitive ion channels. However, anatomical reconstruction of the proprioceptors and connected tendons revealed major biomechanical differences between subtypes. We built a model of the proprioceptors and tendons that identified a biomechanical mechanism for joint angle selectivity and predicted the existence of a topographic map of joint angle, which we confirmed using calcium imaging. Our findings suggest that biomechanical specialization is a key determinant of proprioceptor feature selectivity in Drosophila. More broadly, the discovery of proprioceptive maps reveals common organizational principles between proprioception and other topographically organized sensory systems.

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    08/03/23 | Lysosomal release of amino acids at ER three-way junctions regulates transmembrane and secretory protein mRNA translation.
    Choi H, Liao Y, Yoon YJ, Grimm J, Lavis LD, Singer RH, Lippincott-Schwartz J
    bioRxiv. 2023 Aug 03:. doi: 10.1101/2023.08.01.551382

    One-third of the mammalian proteome is comprised of transmembrane and secretory proteins that are synthesized on endoplasmic reticulum (ER). Here, we investigate the spatial distribution and regulation of mRNAs encoding these membrane and secretory proteins (termed "secretome" mRNAs) through live cell, single molecule tracking to directly monitor the position and translation states of secretome mRNAs on ER and their relationship to other organelles. Notably, translation of secretome mRNAs occurred preferentially near lysosomes on ER marked by the ER junction-associated protein, Lunapark. Knockdown of Lunapark reduced the extent of secretome mRNA translation without affecting translation of other mRNAs. Less secretome mRNA translation also occurred when lysosome function was perturbed by raising lysosomal pH or inhibiting lysosomal proteases. Secretome mRNA translation near lysosomes was enhanced during amino acid deprivation. Addition of the integrated stress response inhibitor, ISRIB, reversed the translation inhibition seen in Lunapark knockdown cells, implying an eIF2 dependency. Altogether, these findings uncover a novel coordination between ER and lysosomes, in which local release of amino acids and other factors from ER-associated lysosomes patterns and regulates translation of mRNAs encoding secretory and membrane proteins.

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    08/02/23 | Investigating the composition and recruitment of the mycobacterial ImuA'-ImuB-DnaE2 mutasome.
    Gessner S, Martin ZA, Reiche MA, Santos JA, Dinkele R, Ramudzuli A, Dhar N, de Wet TJ, Anoosheh S, Lang DM, Aaron J, Chew T, Herrmann J, Müller R, McKinney JD, Woodgate R, Mizrahi V, Venclovas Č, Lamers MH, Warner DF
    eLife. 2023 Aug 02;12:. doi: 10.7554/eLife.75628

    A DNA damage-inducible mutagenic gene cassette has been implicated in the emergence of drug resistance in during anti-tuberculosis (TB) chemotherapy. However, the molecular composition and operation of the encoded 'mycobacterial mutasome' - minimally comprising DnaE2 polymerase and ImuA' and ImuB accessory proteins - remain elusive. Following exposure of mycobacteria to DNA damaging agents, we observe that DnaE2 and ImuB co-localize with the DNA polymerase III β subunit (β clamp) in distinct intracellular foci. Notably, genetic inactivation of the mutasome in an mutant containing a disrupted β clamp-binding motif abolishes ImuB-β clamp focus formation, a phenotype recapitulated pharmacologically by treating bacilli with griselimycin and in biochemical assays in which this β clamp-binding antibiotic collapses pre-formed ImuB-β clamp complexes. These observations establish the essentiality of the ImuB-β clamp interaction for mutagenic DNA repair in mycobacteria, identifying the mutasome as target for adjunctive therapeutics designed to protect anti-TB drugs against emerging resistance.

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    08/01/23 | Organizing memories for generalization in complementary learning systems.
    Weinan Sun , Madhu Advani , Nelson Spruston , Andrew Saxe , James E. Fitzgerald
    Nature Neuroscience. 2023 Aug 01;26(8):1438-1448. doi: 10.1038/s41593-023-01382-9

    Our ability to remember the past is essential for guiding our future behavior. Psychological and neurobiological features of declarative memories are known to transform over time in a process known as systems consolidation. While many theories have sought to explain the time-varying role of hippocampal and neocortical brain areas, the computational principles that govern these transformations remain unclear. Here we propose a theory of systems consolidation in which hippocampal-cortical interactions serve to optimize generalizations that guide future adaptive behavior. We use mathematical analysis of neural network models to characterize fundamental performance tradeoffs in systems consolidation, revealing that memory components should be organized according to their predictability. The theory shows that multiple interacting memory systems can outperform just one, normatively unifying diverse experimental observations and making novel experimental predictions. Our results suggest that the psychological taxonomy and neurobiological organization of declarative memories reflect a system optimized for behaving well in an uncertain future.

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    07/29/23 | Network Statistics of the Whole-Brain Connectome of Drosophila
    Albert Lin , Runzhe Yang , Sven Dorkenwald , Arie Matsliah , Amy R. Sterling , Philipp Schlegel , Szi-chieh Yu , Claire E. McKellar , Marta Costa , Katharina Eichler , Alexander Shakeel Bates , Nils Eckstein , Jan Funke , Gregory S.X.E. Jefferis , Mala Murthy
    bioRxiv. 2023 Jul 29:. doi: 10.1101/2023.07.29.551086

    Animal brains are complex organs composed of thousands of interconnected neurons. Characterizing the network properties of these brains is a requisite step towards understanding mechanisms of computation and information flow. With the completion of the Flywire project, we now have access to the connectome of a complete adult Drosophila brain, containing 130,000 neurons and millions of connections. Here, we present a statistical summary and data products of the Flywire connectome, delving into its network properties and topological features. To gain insights into local connectivity, we computed the prevalence of two- and three-node network motifs, examined their strengths and neurotransmitter compositions, and compared these topological metrics with wiring diagrams of other animals. We uncovered a population of highly connected neurons known as the “rich club” and identified subsets of neurons that may serve as integrators or broadcasters of signals. Finally, we examined subnetworks based on 78 anatomically defined brain regions. The freely available data and neuron populations presented here will serve as a foundation for models and experiments exploring the relationship between neural activity and anatomical structure.

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    07/28/23 | Rastermap: a discovery method for neural population recordings
    Carsen Stringer , Lin Zhong , Atika Syeda , Fengtong Du , Marius Pachitariu
    bioRxiv. 2023 Jul 28:. doi: 10.1101/2023.07.25.550571

    Neurophysiology has long progressed through exploratory experiments and chance discoveries. Anecdotes abound of researchers setting up experiments while listening to spikes in real time and observing a pattern of consistent firing when certain stimuli or behaviors happened. With the advent of large-scale recordings, such close observation of data has become harder because high-dimensional spaces are impenetrable to our pattern-finding intuitions. To help ourselves find patterns in neural data, our lab has been openly developing a visualization framework known as “Rastermap” over the past five years. Rastermap takes advantage of a new global optimization algorithm for sorting neural responses along a one-dimensional manifold. Displayed as a raster plot, the sorted neurons show a variety of activity patterns, which can be more easily identified and interpreted. We first benchmark Rastermap on realistic simulations with multiplexed cognitive variables. Then we demonstrate it on recordings of tens of thousands of neurons from mouse visual and sensorimotor cortex during spontaneous, stimulus-evoked and task-evoked epochs, as well as on whole-brain zebrafish recordings, widefield calcium imaging data, population recordings from rat hippocampus and artificial neural networks. Finally, we illustrate high-dimensional scenarios where Rastermap and similar algorithms cannot be used effectively.

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    07/22/23 | Dissecting Cell Plate Development During Plant Cytokinesis.
    Sinclair R, Cox D, Heddleston J, Aaron J, Wait E, Wilkop T, Drakakaki G
    Microscopy and Microanalysis. 2023 Jul 22;29(Supplement_1):865. doi: 10.1093/micmic/ozad067.428