@article {70329, title = {Unstructured transcription factor interactions enable emergent specificity.}, journal = {Science}, year = {2026}, month = {2026 Mar 19}, pages = {eaeb6487}, abstract = {

How intrinsically disordered regions (IDRs) influence chromatin binding and nuclear organization of transcription factors (TFs) remains unclear. We employed proximity-assisted photoactivation (PAPA), a single-molecule protein-protein interaction sensor, to investigate how IDRs might influence TF interactions with each other and with chromatin in live cells. We found that the Sp1 DNA binding domain (DBD) interacted poorly with chromatin and did not colocalize with Sp1. Weak interaction of the isolated IDR with full-length Sp1 was enhanced by fusion to various unrelated DBDs. Live imaging of polytene chromosomes confirmed that an IDR could confer sharp locus specificity on an otherwise nonspecific DBD. These findings suggest that TF specificity emerges on chromatin when ensembles of diverse, unstructured interactions are scaffolded by transient DNA contacts.

}, issn = {1095-9203}, doi = {10.1126/science.aeb6487}, url = {https://doi.org/10.1126/science.aeb6487}, author = {Abidi, Abrar A and Cattoglio, Claudia and Tang, Natalie N and Fan, Vinson B and Dailey, Gina M and Hay, Amir D and Kunamaneni, Prasanthi and Milkie, Daniel E and Darzacq, Xavier and Betzig, Eric and Tjian, Robert and Graham, Thomas G W} } @article {70133, title = {Ultra-high-density Neuropixels probes improve detection and identification in neuronal recordings.}, journal = {Neuron}, volume = {113}, year = {2025}, month = {2025 Dec 3}, abstract = {

To understand the neural basis of behavior, it is essential to sensitively and accurately measure neural activity at single-neuron and single-spike resolution. Extracellular electrophysiology delivers this, but it has biases in the neurons it detects and it imperfectly resolves their action potentials. To minimize these limitations, we developed a silicon probe with much smaller and denser recording sites than previous designs, called Neuropixels Ultra (NP Ultra). Using NP Ultra, neuronal yield in mouse visual cortex recordings increased by more than 2-fold. With ultra-high spatial resolution, we discovered that a feature of extracellular waveforms, the spatial extent or "footprint," distinguished axonal from somatic recordings. In addition, three genetically identified cortical cell types could be discriminated from one another with \~{}80\% accuracy and from other neurons with \~{}85\% accuracy. NP Ultra improves yield, detection of subcellular compartments, and cell type identification to enable a more powerful dissection of neural circuit activity during behavior.

bioRxiv preprint: doi.org/10.1101/2023.08.23.554527

}, issn = {1097-4199}, doi = {10.1016/j.neuron.2025.08.030}, url = {https://doi.org/10.1016/j.neuron.2025.08.030}, author = {Ye, Zhiwen and Shelton, Andrew M and Shaker, Jordan R and Boussard, Julien and Colonell, Jennifer and Birman, Daniel and Manavi, Sahar and Chen, Susu and Windolf, Charlie and Hurwitz, Cole and Yu, Han and Namima, Tomoyuki and Pedraja, Federico and Weiss, Shahaf and Raducanu, Bogdan C and Ness, Torbj{\o}rn V and Jia, Xiaoxuan and Mastroberardino, Giulia and Rossi, L Federico and Carandini, Matteo and H{\"a}usser, Michael and Einevoll, Gaute T and Laurent, Gilles and Sawtell, Nathaniel B and Bair, Wyeth and Pasupathy, Anitha and Mora Lopez, Carolina and Dutta, Barundeb and Paninski, Liam and Siegle, Joshua H and Koch, Christof and Olsen, Shawn R and Harris, Timothy D and Steinmetz, Nicholas A} } @article {70212, title = {Uncertainty quantification for connectomics.}, journal = {Nat Methods}, volume = {22}, year = {2025}, month = {2025 Dec 08}, pages = {2484-2486}, abstract = {

No abstract available.

}, issn = {1548-7105}, doi = {10.1038/s41592-025-02945-3}, url = {https://doi.org/10.1038/s41592-025-02945-3}, author = {Funke, Jan} } @article {69914, title = {Unlocking in vivo metabolic insights with vibrational microscopy.}, journal = {Nat Methods}, volume = {22}, year = {2025}, month = {2025 May 13}, pages = {886-889}, abstract = {

No abstract available.

}, issn = {1548-7105}, doi = {10.1038/s41592-025-02616-3}, url = {https://doi.org/10.1038/s41592-025-02616-3}, author = {Chen, Tao and Savini, Marzia and Wang, Meng C} } @article {69913, title = {Unlocking in vivo metabolic insights with vibrational microscopy.}, journal = {Nat Methods}, volume = {22}, year = {2025}, month = {2025 May 13}, pages = {886-889}, issn = {1548-7105}, doi = {10.1038/s41592-025-02616-3}, url = {https://doi.org/10.1038/s41592-025-02616-3}, author = {Chen, Tao and Savini, Marzia and Wang, Meng C} } @article {69228, title = {Unsupervised pretraining in biological neural networks}, journal = {Nature}, year = {2025}, month = {2025 Jun 18}, abstract = {

Representation learning in neural networks may be implemented with supervised or unsupervised algorithms, distinguished by the availability of instruction. In the sensory cortex, perceptual learning drives neural plasticity1-13, but it is not known whether this is due to supervised or unsupervised learning. Here we recorded populations of up to 90,000 neurons simultaneously from the primary visual cortex (V1) and higher visual areas (HVAs) while mice learned multiple tasks, as well as during unrewarded exposure to the same stimuli. Similar to previous studies, we found that neural changes in task mice were correlated with their behavioural learning. However, the neural changes were mostly replicated in mice with unrewarded exposure, suggesting that the changes were in fact due to unsupervised learning. The neural plasticity was highest in the medial HVAs and obeyed visual, rather than spatial, learning rules. In task mice only, we found a ramping reward-prediction signal in anterior HVAs, potentially involved in supervised learning. Our neural results predict that unsupervised learning may accelerate subsequent task learning, a prediction that we validated with behavioural experiments.

Preprint:\ https://www.biorxiv.org/content/early/2024/02/27/2024.02.25.581990

}, doi = {10.1038/s41586-025-09180-y}, url = {https://doi.org/10.1038/s41586-025-09180-y}, author = {Lin Zhong and Scott Baptista and Rachel Gattoni and Jon Arnold and Daniel Flickinger and Carsen Stringer and Marius Pachitariu} } @article {70123, title = {An updated catalogue of split-GAL4 driver lines for descending neurons in Drosophila melanogaster}, journal = {eLife}, year = {2025}, month = {2025 Sept 19}, abstract = {

Descending neurons (DNs) occupy a key position in the sensorimotor hierarchy, conveying signals from the brain to the rest of the body below the neck. In\ Drosophila melanogaster\ flies, approximately 480 DN cell types have been described from electron-microscopy image datasets. Genetic access to these cell types is crucial for further investigation of their role in generating behaviour. We previously conducted the first large-scale survey of\ Drosophila melanogaster\ DNs, describing 98 unique cell types from light microscopy and generating cell-type-specific split-Gal4 driver lines for 65 of them. Here, we extend our previous work, describing the morphology of 146 additional DN types from light microscopy, bringing the total number DN types identified in light microscopy datasets to 244, or roughly 50\% of all DN types. In addition, we produced 500 new sparse split-Gal4 driver lines and compiled a list of previously published DN lines from the literature for a combined list of 806 split-Gal4 driver lines targeting 190 DN types.

}, doi = {10.7554/elife.107450.1}, url = {http://dx.doi.org/10.7554/eLife.107450.1}, author = {Zung, Jessica L and Namiki, Shigehiro and Meissner, Geoffrey W and Cheong, Han Sj and Costa, Marta and Eichler, Katharina and St{\"u}rner, Tomke and Jefferis, Gregory Sxe and Managan, Claire and Korff, Wyatt and Card, Gwyneth M} } @article {69790, title = {An updated catalogue of split-GAL4 driver lines for descending neurons in Drosophila melanogaster}, journal = {bioRxiv}, year = {2025}, month = {2025 Feb 24}, abstract = {

Descending neurons (DNs) occupy a key position in the sensorimotor hierarchy, conveying signals from the brain to the rest of the body below the neck. In Drosophila melanogaster flies, approximately 480 DN cell types have been described from electron-microscopy image datasets. Genetic access to these cell types is crucial for further investigation of their role in generating behaviour. We previously conducted the first large-scale survey of Drosophila melanogaster DNs, describing 98 unique cell types from light microscopy and generating cell-type-specific split-Gal4 driver lines for 65 of them. Here, we extend our previous work, describing the morphology of 137 additional DN types from light microscopy, bringing the total number DN types identified in light microscopy datasets to 235, or nearly 50\%. In addition, we produced 500 new sparse split-Gal4 driver lines and compiled a list of previously published DN lines from the literature for a combined list of 738 split-Gal4 driver lines targeting 171 DN types.

}, doi = {10.1101/2025.02.22.639679}, url = {https://www.biorxiv.org/content/early/2025/02/24/2025.02.22.639679}, author = {Zung, Jessica L. and Namiki, Shigehiro and Meissner, Geoffrey W. and Costa, Marta and Eichler, Katharina and St{\"u}rner, Tomke and Jefferis, Gregory S.X.E. and Managan, Claire and FlyLight Project Team and Korff, Wyatt and Card, Gwyneth M.} } @article {69350, title = {Ultra-high density electrodes improve detection, yield, and cell type identification in neuronal recordings}, journal = {bioRxiv}, year = {2024}, month = {2024 Apr 10}, abstract = {

To understand the neural basis of behavior, it is essential to sensitively and accurately measure neural activity at single neuron and single spike resolution. Extracellular electrophysiology delivers this, but it has biases in the neurons it detects and it imperfectly resolves their action potentials. To minimize these limitations, we developed a silicon probe with much smaller and denser recording sites than previous designs, called Neuropixels Ultra (NP Ultra). This device samples neuronal activity at ultra-high spatial density ( 10 times higher than previous probes) with low noise levels, while trading off recording span. NP Ultra is effectively an implantable voltage-sensing camera that captures a planar image of a neuron{\textquoteright}s electrical field. We use a spike sorting algorithm optimized for these probes to demonstrate that the yield of visually-responsive neurons in recordings from mouse visual cortex improves up to 3-fold. We show that NP Ultra can record from small neuronal structures including axons and dendrites. Recordings across multiple brain regions and four species revealed a subset of extracellular action potentials with unexpectedly small spatial spread and axon-like features. We share a large-scale dataset of these brain-wide recordings in mice as a resource for studies of neuronal biophysics. Finally, using ground-truth identification of three major inhibitory cortical cell types, we found that these cell types were discriminable with approximately 75\% success, a significant improvement over lower-resolution recordings. NP Ultra improves spike sorting performance, detection of subcellular compartments, and cell type classification to enable more powerful dissection of neural circuit activity during behavior.

}, doi = {10.1101/2023.08.23.554527}, url = {https://www.biorxiv.org/content/early/2024/04/10/2023.08.23.554527}, author = {Zhiwen Ye and Andrew M Shelton and Jordan R Shaker and Julien M Boussard and Jennifer Colonell and Daniel Birman and Sahar Manavi and Susu Chen and Charlie Windolf and Cole Hurwitz and Tomoyuki Namima and Frederico Pedraja and Shahaf Weiss and Bogdan Raducanu and Torbj{\o}rn Ness and Xiaoxuan Jia and Giulia Mastroberardino and L. Federico Rossi and Matteo Carandini and Michael Hausser and Gaute T Einevoll and Gilles Laurent and Nathaniel B Sawtell and Wyeth Bair and Anitha Pasupathy and Carolina Mora-Lopez and Barun Dutta and Liam Paninski and Joshua H Siegle and Christof Koch and Shawn R Olsen and Timothy D Harris and Nicholas A Steinmetz} } @article {69459, title = {Ultrastructural differences impact cilia shape and external exposure across cell classes in the visual cortex}, journal = {Curr Biol}, year = {2024}, month = {2024 May 13}, abstract = {

A primary cilium is a membrane-bound extension from the cell surface that contains receptors for perceiving and transmitting signals that modulate cell state and activity. Primary cilia in the brain are less accessible than cilia on cultured cells or epithelial tissues because in the brain they protrude into a deep, dense network of glial and neuronal processes. Here, we investigated cilia frequency, internal structure, shape, and position in large, high-resolution transmission electron microscopy volumes of mouse primary visual cortex. Cilia extended from the cell bodies of nearly all excitatory and inhibitory neurons, astrocytes, and oligodendrocyte precursor cells (OPCs) but were absent from oligodendrocytes and microglia. Ultrastructural comparisons revealed that the base of the cilium and the microtubule organization differed between neurons and glia. Investigating cilia-proximal features revealed that many cilia were directly adjacent to synapses, suggesting that cilia are poised to encounter locally released signaling molecules. Our analysis indicated that synapse proximity is likely due to random encounters in the neuropil, with no evidence that cilia modulate synapse activity as would be expected in tetrapartite synapses. The observed cell class differences in proximity to synapses were largely due to differences in external cilia length. Many key structural features that differed between neuronal and glial cilia influenced both cilium placement and shape and, thus, exposure to processes and synapses outside the cilium. Together, the ultrastructure both within and around neuronal and glial cilia suggest differences in cilia formation and function across cell types in the brain.

}, issn = {1879-0445}, doi = {10.1016/j.cub.2024.04.043}, author = {Ott, Carolyn M and Torres, Russel and Kuan, Tung-Sheng and Kuan, Aaron and Buchanan, JoAnn and Elabbady, Leila and Seshamani, Sharmishtaa and Bodor, Agnes L and Collman, Forrest and Bock, Davi D and Lee, Wei Chung and da Costa, Nuno Ma{\c c}arico and Lippincott-Schwartz, Jennifer} } @article {68968, title = {Ultra-high density electrodes improve detection, yield, and cell type specificity of brain recordings.}, journal = {bioRxiv}, year = {2023}, month = {2023 Aug 25}, abstract = {

To study the neural basis of behavior, we require methods to sensitively and accurately measure neural activity at single neuron and single spike resolution. Extracellular electrophysiology is a principal method for achieving this, but it has biases in the neurons it detects and it imperfectly resolves their action potentials. To overcome these limitations, we developed a silicon probe with significantly smaller and denser recording sites than previous designs, called Neuropixels Ultra (NP Ultra). This device measures neuronal activity at ultra-high densities (\>1300 sites per mm, 10 times higher than previous probes), with 6 {\textmu}m center-to-center spacing and low noise. This device effectively comprises an implantable voltage-sensing camera that captures a planar image of a neuron{\textquoteright}s electrical field. We introduce a new spike sorting algorithm optimized for these probes and use it to find that the yield of visually-responsive neurons in recordings from mouse visual cortex improves \~{}3-fold. Recordings across multiple brain regions and four species revealed a subset of unexpectedly small extracellular action potentials not previously reported. Further experiments determined that, in visual cortex, these do not correspond to major subclasses of interneurons and instead likely reflect recordings from axons. Finally, using ground-truth identification of cortical inhibitory cell types with optotagging, we found that cell type was discriminable with approximately 75\% success among three types, a significant improvement over lower-resolution recordings. NP Ultra improves spike sorting performance, sampling bias, and cell type classification.

}, doi = {10.1101/2023.08.23.554527}, author = {Ye, Zhiwen and Shelton, Andrew M and Shaker, Jordan R and Boussard, Julien and Colonell, Jennifer and Manavi, Sahar and Chen, Susu and Windolf, Charlie and Hurwitz, Cole and Namima, Tomoyuki and Pedraja, Federico and Weiss, Shahaf and Raducanu, Bogdan and Ness, Torbj{\o}rn V and Einevoll, Gaute T and Laurent, Gilles and Sawtell, Nathaniel B and Bair, Wyeth and Pasupathy, Anitha and Mora Lopez, Carolina and Dutta, Barun and Paninski, Liam and Siegle, Joshua H and Koch, Christof and Olsen, Shawn R and Harris, Timothy D and Steinmetz, Nicholas A} } @conference {69206, title = {Unsupervised Learning of Object-Centric Embeddings for Cell Instance Segmentation in Microscopy Images}, booktitle = {2023 IEEE/CVF International Conference on Computer Vision (ICCV)}, year = {2023}, month = {2023 Oct 01}, publisher = {IEEE}, organization = {IEEE}, address = {Paris, France}, abstract = {

Segmentation of objects in microscopy images is required for many biomedical applications. We introduce object-centric embeddings (OCEs), which embed image patches such that the spatial offsets between patches cropped from the same object are preserved. Those learnt embeddings can be used to delineate individual objects and thus obtain instance segmentations. Here, we show theoretically that, under assumptions commonly found in microscopy images, OCEs can be learnt through a self-supervised task that predicts the spatial offset between image patches. Together, this forms an unsupervised cell instance segmentation method which we evaluate on nine diverse large-scale microscopy datasets. Segmentations obtained with our method lead to substantially improved results, compared to state-of-the-art baselines on six out of nine datasets, and perform on par on the remaining three datasets. If ground-truth annotations are available, our method serves as an excellent starting point for supervised training, reducing the required amount of ground-truth needed by one order of magnitude, thus substantially increasing the practical applicability of our method. Source code is available at github.com/funkelab/cellulus.

}, doi = {10.1109/ICCV51070.2023.01944}, url = {https://ieeexplore.ieee.org/document/10377649/}, author = {Wolf, Steffen and Lalit, Manan and McDole, Katie and Funke, Jan} } @article {68250, title = {Using Simulated Training Data of Voxel-Level Generative Models to Improve 3D Neuron Reconstruction.}, journal = {IEEE Transactions on Medical Imaging}, volume = {PP}, year = {2022}, month = {2022 Jul 14}, abstract = {

Reconstructing neuron morphologies from fluorescence microscope images plays a critical role in neuroscience studies. It relies on image segmentation to produce initial masks either for further processing or final results to represent neuronal morphologies. This has been a challenging step due to the variation and complexity of noisy intensity patterns in neuron images acquired from microscopes. Whereas progresses in deep learning have brought the goal of accurate segmentation much closer to reality, creating training data for producing powerful neural networks is often laborious. To overcome the difficulty of obtaining a vast number of annotated data, we propose a novel strategy of using two-stage generative models to simulate training data with voxel-level labels. Trained upon unlabeled data by optimizing a novel objective function of preserving predefined labels, the models are able to synthesize realistic 3D images with underlying voxel labels. We showed that these synthetic images could train segmentation networks to obtain even better performance than manually labeled data. To demonstrate an immediate impact of our work, we further showed that segmentation results produced by networks trained upon synthetic data could be used to improve existing neuron reconstruction methods.

}, issn = {1558-254X}, doi = {10.1109/TMI.2022.3191011}, author = {Liu, Chao and Wang, Deli and Zhang, Han and Wu, Wei and Sun, Wenzhi and Zhao, Ting and Zheng, Nenggan} } @article {67845, title = {Unraveling Single-Particle Trajectories Confined in Tubular Networks}, journal = {arXiv}, year = {2021}, month = {2021 Dec 11}, abstract = {

The analysis of single particle trajectories plays an important role in elucidating dynamics within complex environments such as those found in living cells. However, the characterization of intracellular particle motion is often confounded by confinement of the particles within non-trivial subcellular geometries. Here, we focus specifically on the case of particles undergoing Brownian motion within a tubular network, as found in some cellular organelles. An unraveling algorithm is developed to uncouple particle motion from the confining network structure, allowing for an accurate extraction of the diffusion coefficient, as well as differentiating between Brownian and fractional Brownian dynamics. We validate the algorithm with simulated trajectories and then highlight its application to an example system: analyzing the motion of membrane proteins confined in the tubules of the peripheral endoplasmic reticulum in mammalian cells. We show that these proteins undergo diffusive motion with a well-characterized diffusivity. Our algorithm provides a generally applicable approach for disentangling geometric morphology and particle dynamics in networked architectures.

}, url = {https://arxiv.org/abs/2112.05884}, author = {Yunhao Sun and Zexi Yu and Christopher Obara and Keshav Mittal and Jennifer Lippincott-Schwarz and Elena F Koslover} } @article {67310, title = {Unveiling the sensory and interneuronal pathways of the neuroendocrine connectome in Drosophila.}, journal = {eLife}, volume = {10}, year = {2021}, month = {2021 Jun 04}, abstract = {

Neuroendocrine systems in animals maintain organismal homeostasis and regulate stress response. Although a great deal of work has been done on the neuropeptides and hormones that are released and act on target organs in the periphery, the synaptic inputs onto these neuroendocrine outputs in the brain are less well understood. Here, we use the transmission electron microscopy reconstruction of a whole central nervous system in the larva to elucidate the sensory pathways and the interneurons that provide synaptic input to the neurosecretory cells projecting to the endocrine organs. Predicted by network modeling, we also identify a new carbon dioxide-responsive network that acts on a specific set of neurosecretory cells and that includes those expressing corazonin (Crz) and diuretic hormone 44 (Dh44) neuropeptides. Our analysis reveals a neuronal network architecture for combinatorial action based on sensory and interneuronal pathways that converge onto distinct combinations of neuroendocrine outputs.

}, issn = {2050-084X}, doi = {10.7554/eLife.65745}, author = {H{\"u}ckesfeld, Sebastian and Schlegel, Philipp and Miroschnikow, Anton and Schoofs, Andreas and Zinke, Ingo and Haubrich, Andr{\'e} N and Schneider-Mizell, Casey M and Truman, James W and Fetter, Richard D and Cardona, Albert and Pankratz, Michael J} } @article {65603, title = {Ultrastructural visualization of 3D chromatin folding using volume electron microscopy and DNA in situ hybridization.}, journal = {Nature Communications}, volume = {11}, year = {2020}, month = {2020 May 01}, pages = {2120}, abstract = {

The human genome is extensively folded into 3-dimensional organization. However, the detailed 3D chromatin folding structures have not been fully visualized due to the lack of robust and ultra-resolution imaging capability. Here, we report the development of an electron microscopy method that combines serial block-face scanning electron microscopy with in situ hybridization (3D-EMISH) to visualize 3D chromatin folding at targeted genomic regions with ultra-resolution (5 {\texttimes} 5 {\texttimes} 30 nm in xyz dimensions) that is superior to the current super-resolution by fluorescence light microscopy. We apply 3D-EMISH to human lymphoblastoid cells at a 1.7 Mb segment of the genome and visualize a large number of distinctive 3D chromatin folding structures in ultra-resolution. We further quantitatively characterize the reconstituted chromatin folding structures by identifying sub-domains, and uncover a high level heterogeneity of chromatin folding ultrastructures in individual nuclei, suggestive of extensive dynamic fluidity in 3D chromatin states.

}, issn = {2041-1723}, doi = {10.1038/s41467-020-15987-2}, author = {Trzaskoma, Pawe{\l} and Ruszczycki, B{\l}a{\.z}ej and Lee, Byoungkoo and Pels, Katarzyna K and Krawczyk, Katarzyna and Bokota, Grzegorz and Szczepankiewicz, Andrzej A and Aaron, Jesse and Walczak, Agnieszka and {\'S}liwi{\'n}ska, Ma{\l}gorzata A and Magalska, Adriana and Kadlof, Michal and Wolny, Artur and Parteka, Zofia and Arabasz, Sebastian and Kiss-Arabasz, Magdalena and Plewczy{\'n}ski, Dariusz and Ruan, Yijun and Wilczy{\'n}ski, Grzegorz M} } @article {65597, title = {Unanticipated stressful and rewarding experiences engage the same prefrontal cortex and ventral tegmental area neuronal populations.}, journal = {eNeuro}, year = {2020}, month = {2020 May 08}, abstract = {

Brain networks that mediate motivated behavior in the context of aversive and rewarding experiences involve the prefrontal cortex (PFC) and ventral tegmental area (VTA). Neurons in both regions are activated by stress and reward, and by learned cues that predict aversive or appetitive outcomes. Recent studies have proposed that separate neuronal populations and circuits in these regions encode learned aversive versus appetitive contexts. But how about the actual experience? Do the same or different PFC and VTA neurons encode unanticipated aversive and appetitive experiences? To address this, we recorded unit activity and local field potentials (LFP) in the dorsomedial PFC (dmPFC) and VTA of male rats as they were exposed, in the same recording session, to reward (sucrose) or stress (tail pinch) spaced one hour apart. As expected, experience-specific neuronal responses were observed. About 15-25\% of single units in each region responded by excitation or inhibition to either stress or reward, and only stress increased LFP theta oscillation power in both regions and coherence between regions. But the largest number of responses (29\% dmPFC and 30\% VTA units) involved dual-valence neurons that responded to both stress and reward exposure. Moreover, the temporal profile of neuronal population activity in dmPFC and VTA as assessed by principal component analysis were similar during both types of experiences. These results reveal that aversive and rewarding experiences engage overlapping neuronal populations in the dmPFC and the VTA. These populations may provide a locus of vulnerability for stress related disorders, which are often associated with anhedonia. Animals must recognize unexpected harmful and rewarding events in order to survive. How the brain represents these competing experiences is not fully understood. Two interconnected brain regions implicated in encoding both rewarding and stressful events are the dmPFC and the VTA. In either region, separate neurons and associated circuitry are assumed to respond to events with positive or negative valence. We find, however, that a significant subpopulation of neurons in dmPFC and VTA encode both rewarding and aversive experiences. These dual-valence neurons may provide a computational advantage for flexible planning of behavior when organisms face unexpected rewarding and harmful experiences.

}, issn = {2373-2822}, doi = {10.1523/ENEURO.0029-20.2020}, author = {Del Arco, Alberto and Park, Junchol and Moghaddam, Bita} } @article {65910, title = {An unbiased template of the Drosophila brain and ventral nerve cord.}, journal = {PLoS One}, volume = {15}, year = {2020}, month = {2020 Dec 31}, pages = {e0236495}, abstract = {

The fruit fly Drosophila melanogaster is an important model organism for neuroscience with a wide array of genetic tools that enable the mapping of individual neurons and neural subtypes. Brain templates are essential for comparative biological studies because they enable analyzing many individuals in a common reference space. Several central brain templates exist for Drosophila, but every one is either biased, uses sub-optimal tissue preparation, is imaged at low resolution, or does not account for artifacts. No publicly available Drosophila ventral nerve cord template currently exists. In this work, we created high-resolution templates of the Drosophila brain and ventral nerve cord using the best-available technologies for imaging, artifact correction, stitching, and template construction using groupwise registration. We evaluated our central brain template against the four most competitive, publicly available brain templates and demonstrate that ours enables more accurate registration with fewer local deformations in shorter time.

}, issn = {1932-6203}, doi = {10.1371/journal.pone.0236495}, author = {Bogovic, John A and Otsuna, Hideo and Heinrich, Larissa and Ito, Masayoshi and Jeter, Jennifer and Meissner, Geoffrey and Nern, Aljoscha and Colonell, Jennifer and Malkesman, Oz and Ito, Kei and Saalfeld, Stephan} } @article {65375, title = {Unc-4 acts to promote neuronal identity and development of the take-off circuit in the Drosophila CNS.}, journal = {eLife}, volume = {9}, year = {2020}, month = {2020 Mar 27}, doi = {10.7554/eLife.55007}, url = {https://elifesciences.org/articles/55007}, author = {Lacin, Haluk and Williamson, W Ryan and Card, Gwyneth M and Skeath, James B and Truman, James W} } @article {64840, title = {Ultrapotent chemogenetics for research and potential clinical applications.}, journal = {Science}, volume = {364}, year = {2019}, month = {2019 Mar 14}, pages = {eaav5282}, abstract = {

Chemogenetics enables non-invasive chemical control over cell populations in behaving animals. However, existing small molecule agonists show insufficient potency or selectivity. There is also need for chemogenetic systems compatible with both research and human therapeutic applications. We developed a new ion channel-based platform for cell activation and silencing that is controlled by low doses of the anti-smoking drug varenicline. We then synthesized novel sub-nanomolar potency agonists, called uPSEMs, with high selectivity for the chemogenetic receptors. uPSEMs and their receptors were characterized in brains of mice and a rhesus monkey by in vivo electrophysiology, calcium imaging, positron emission tomography, behavioral efficacy testing, and receptor counterscreening. This platform of receptors and selective ultrapotent agonists enables potential research and clinical applications of chemogenetics.

}, issn = {1095-9203}, doi = {10.1126/science.aav5282}, author = {Magnus, Christopher J and Lee, Peter H and Bonaventura, Jordi and Zemla, Roland and Gomez, Juan L and Ramirez, Melissa H and Hu, Xing and Galvan, Adriana and Basu, Jayeeta and Michaelides, Michael and Sternson, Scott M} } @article {65078, title = {Unlimited genetic switches for cell-type-specific manipulation.}, journal = {Neuron}, volume = {104}, year = {2019}, month = {2019 Oct 23}, pages = {227-38}, abstract = {

Gaining independent genetic access to discrete cell types is critical to interrogate their biological functions as well as to deliver precise gene therapy. Transcriptomics has allowed us to profile cell populations with extraordinary precision, revealing that cell types are typically defined by a unique combination of genetic markers. Given the lack of adequate tools to target cell types based on multiple markers, most cell types remain inaccessible to genetic manipulation. Here we present CaSSA, a platform to create unlimited genetic switches based on CRISPR/Cas9 (Ca) and the DNA repair mechanism known as single-strand annealing (SSA). CaSSA allows engineering of independent genetic switches, each responding to a specific gRNA. Expressing multiple gRNAs in specific patterns enables multiplex cell-type-specific manipulations and combinatorial genetic targeting. CaSSA is a new genetic tool that conceptually works as an unlimited number of recombinases and will facilitate genetic access to cell types in diverse organisms.

}, doi = {https://doi.org/10.1016/j.neuron.2019.07.005}, author = {Garcia-Marques, Jorge and Yang, Ching-Po and Isabel Espinosa Medina and Mok, Kent and Koyama, Minoru and Lee, Tzumin} } @article {65093, title = {Ultralarge modulation of fluorescence by neuromodulators in carbon nanotubes functionalized with self-assembled oligonucleotide rings.}, journal = {Nano Letters}, volume = {18}, year = {2018}, month = {2018 Nov 14}, pages = {6995-7003}, abstract = {

Noncovalent interactions between single-stranded DNA (ssDNA) oligonucleotides and single wall carbon nanotubes (SWNTs) have provided a unique class of tunable chemistries for a variety of applications. However, mechanistic insight into both the photophysical and intermolecular phenomena underlying their utility is lacking, which results in obligate heuristic approaches for producing ssDNA-SWNT based technologies. In this work, we present an ultrasensitive "turn-on" nanosensor for neuromodulators dopamine and norepinephrine with strong relative change in fluorescence intensity (Δ F/ F) of up to 3500\%, a signal appropriate for in vivo neuroimaging, and uncover the photophysical principles and intermolecular interactions that govern the molecular recognition and fluorescence modulation of this nanosensor synthesized from the spontaneous self-assembly of (GT) ssDNA rings on SWNTs. The fluorescence modulation of the ssDNA-SWNT conjugate is shown to exhibit remarkable sensitivity to the ssDNA sequence chemistry, length, and surface density, providing a set of parameters with which to tune nanosensor dynamic range, analyte selectivity\ and strength of fluorescence turn-on. We employ classical and quantum mechanical molecular dynamics simulations to rationalize our experimental findings. Calculations show that (GT) ssDNA form ordered rings around (9,4)\ SWNTs, inducing periodic surface potentials that modulate exciton recombination lifetimes. Further evidence is presented to elucidate how dopamine analyte binding modulates SWNT fluorescence. We discuss the implications of our findings for SWNT-based molecular imaging applications.

}, keywords = {Biosensing Techniques, DNA, Single-Stranded, Dopamine, Fluorescence, Nanotubes, Carbon, Neurotransmitter Agents, Norepinephrine, Oligonucleotides}, issn = {1530-6992}, doi = {10.1021/acs.nanolett.8b02937}, author = {Beyene, Abraham G and Alizadehmojarad, Ali A and Dorlhiac, Gabriel and Goh, Natalie and Streets, Aaron M and Kr{\'a}l, Petr and Vukovi{\'c}, Lela and Landry, Markita P} } @article {49386, title = {An unbiased template of the Drosophila brain and ventral nerve cord.}, journal = {bioRxiv}, year = {2018}, month = {2018 Jul 25}, abstract = {

The fruit fly Drosophila melanogaster is an important model organism for neuroscience with a wide array of genetic tools that enable the mapping of individuals neurons and neural subtypes. Brain templates are essential for comparative biological studies because they enable analyzing many individuals in a common reference space. Several central brain templates exist for Drosophila, but every one is either biased, uses sub-optimal tissue preparation, is imaged at low resolution, or does not account for artifacts. No publicly available Drosophila ventral nerve cord template currently exists. In this work, we created high-resolution templates of the Drosophila brain and ventral nerve cord using the best-available technologies for imaging, artifact correction, stitching, and template construction using groupwise registration. We evaluated our central brain template against the four most competitive, publicly available brain templates and demonstrate that ours enables more accurate registration with fewer local deformations in shorter time.

}, doi = {10.1101/376384}, author = {Bogovic, John A and Otsuna, Hideo and Heinrich, Larissa and Ito, Masayoshi and Jeter, Jennifer and Meissner, Geoffrey W and Nern, Aljoscha and Colonell, Jennifer and Malkesman, Oz and Saalfeld, Stephan} } @article {49120, title = {Unnecessary tension.}, journal = {Lab Animal}, volume = {47}, year = {2018}, month = {2018 Apr}, pages = {91}, issn = {1548-4475}, doi = {10.1038/s41684-018-0024-9}, author = {Cox, James D and Seltzer, Meghan J} } @article {48934, title = {Ultra-selective looming detection from radial motion opponency.}, journal = {Nature}, volume = {551}, year = {2017}, month = {2017 Nov 08}, pages = {237-241}, abstract = {

Nervous systems combine lower-level sensory signals to detect higher-order stimulus features critical to survival, such as the visual looming motion created by an imminent collision or approaching predator. Looming-sensitive neurons have been identified in diverse animal species. Different large-scale visual features such as looming often share local cues, which means loom-detecting neurons face the challenge of rejecting confounding stimuli. Here we report the discovery of an ultra-selective looming detecting neuron, lobula plate/lobula columnar, type II (LPLC2) in Drosophila, and show how its selectivity is established by radial motion opponency. In the fly visual system, directionally selective small-field neurons called T4 and T5 form a spatial map in the lobula plate, where they each terminate in one of four retinotopic layers, such that each layer responds to motion in a different cardinal direction. Single-cell anatomical analysis reveals that each arm of the LPLC2 cross-shaped primary dendrites ramifies in one of these layers and extends along that layer{\textquoteright}s preferred motion direction. In vivo calcium imaging demonstrates that, as their shape predicts, individual LPLC2 neurons respond strongly to outward motion emanating from the centre of the neuron{\textquoteright}s receptive field. Each dendritic arm also receives local inhibitory inputs directionally selective for inward motion opposing the excitation. This radial motion opponency generates a balance of excitation and inhibition that makes LPLC2 non-responsive to related patterns of motion such as contraction, wide-field rotation or luminance change. As a population, LPLC2 neurons densely cover visual space and terminate onto the giant fibre descending neurons, which drive the jump muscle motor neuron to trigger an escape take off. Our findings provide a mechanistic description of the selective feature detection that flies use to discern and escape looming threats.

}, issn = {1476-4687}, doi = {10.1038/nature24626}, author = {Klapoetke, Nathan C and Nern, Aljoscha and Peek, Martin Y and Rogers, Edward M and Breads, Patrick and Rubin, Gerald M and Reiser, Michael B and Card, Gwyneth M} } @article {48513, title = {Unraveling cell-to-cell signaling networks with chemical biology.}, journal = {Nature Chemical Biology}, volume = {13}, year = {2017}, month = {2017 May 17}, pages = {564-568}, issn = {1552-4469}, doi = {10.1038/nchembio.2391}, author = {Gartner, Zev J and Prescher, Jennifer A and Lavis, Luke D} } @article {47972, title = {An unsupervised method for quantifying the behavior of interacting individuals.}, journal = {Physical Biology}, volume = {14}, year = {2016}, month = {2017 Feb16}, pages = {1609.09345}, abstract = {

Behaviors involving the interaction of multiple individuals are complex and frequently crucial for an animal{\textquoteright}s survival. These interactions, ranging across sensory modalities, length scales, and time scales, are often subtle and difficult to characterize. Contextual effects on the frequency of behaviors become even more difficult to quantify when physical interaction between animals interferes with conventional data analysis, e.g. due to visual occlusion. We introduce a method for quantifying behavior in fruit fly interaction that combines high-throughput video acquisition and tracking of individuals with recent unsupervised methods for capturing an animal{\textquoteright}s entire behavioral repertoire. We find behavioral differences between solitary flies and those paired with an individual of the opposite sex, identifying specific behaviors that are affected by social and spatial context. Our pipeline allows for a comprehensive description of the interaction between two individuals using unsupervised machine learning methods, and will be used to answer questions about the depth of complexity and variance in fruit fly courtship.

}, doi = {10.1088/1478-3975/aa5c50}, url = {https://arxiv.org/abs/1609.09345v1}, author = {Klibaite, Ugne and Berman, Gordon J and Cande, Jessica and Stern, David L} } @article {46325, title = {Ultrastructurally smooth thick partitioning and volume stitching for large-scale connectomics.}, journal = {Nature Methods}, volume = {12}, year = {2015}, month = {2015 Feb 16}, pages = {319-22}, abstract = {

Focused-ion-beam scanning electron microscopy (FIB-SEM) has become an essential tool for studying neural tissue at resolutions below 10 nm {\texttimes} 10 nm {\texttimes} 10 nm, producing data sets optimized for automatic connectome tracing. We present a technical advance, ultrathick sectioning, which reliably subdivides embedded tissue samples into chunks (20 μm thick) optimally sized and mounted for efficient, parallel FIB-SEM imaging. These chunks are imaged separately and then {\textquoteright}volume stitched{\textquoteright} back together, producing a final three-dimensional data set suitable for connectome tracing.

}, issn = {1548-7105}, doi = {10.1038/nmeth.3292}, author = {Hayworth, Kenneth J and Xu, C Shan and Lu, Zhiyuan and Knott, Graham W and Fetter, Richard D and Tapia, Juan Carlos and Lichtman, Jeff W and Hess, Harald F} } @proceedings {46519, title = {Understanding classifier errors by examining influential neighbors.}, year = {2015}, month = {06/2015}, publisher = {IEEE}, address = {Boston, MA}, abstract = {

Modern supervised learning algorithms can learn very accurate and complex discriminating functions. But when these classifiers fail, this complexity can also be a drawback because there is no easy, intuitive way to diagnose why they are failing and remedy the problem. This important question has received little attention. To address this problem, we propose a novel method to analyze and understand a classifier{\textquoteright}s errors. Our method centers around a measure of how much influence a training example has on the classifier{\textquoteright}s prediction for a test example. To understand why a classifier is\ mispredicting\ the label of a given test example, the user can find and review the most influential training examples that caused this\ misprediction, allowing them to focus their attention on relevant areas of the data space. This will aid the user in determining if and how the training data is inconsistently labeled or lacking in diversity, or if the feature representation is insufficient. As computing the influence of each training example is computationally impractical, we propose a novel distance metric to approximate influence for boosting classifiers that is fast enough to be used interactively. We also show several novel use paradigms of our distance metric. Through experiments, we show that it can be used to find incorrectly or inconsistently labeled training examples, to find specific areas of the data space that need more training data, and to gain insight into which features are missing from the current representation.\ 

Code is available at\ https://github.com/kristinbranson/InfluentialNeighbors.

}, author = {Mayank Kabra and Alice A. Robie and Kristin Branson} } @article {48277, title = {Unilateral whisker trimming in newborn rats alters neuronal coincident discharge among mature barrel cortex neurons.}, journal = {Journal of neurophysiology}, volume = {112}, year = {2014}, month = {2014 Oct 15}, pages = {1925-35}, abstract = {

It is known that sensory deprivation, including postnatal whisker trimming, can lead to severe deficits in the firing rate properties of cortical neurons. Recent results indicate that development of synchronous discharge among cortical neurons is also activity influenced, and that correlated discharge is significantly impaired following loss of bilateral sensory input in rats. Here we investigate whether unilateral whisker trimming (unilateral deprivation or UD) after birth interferes in the same way with the development of synchronous discharge in cortex. We measured the coincidence of spikes among pairs of neurons recorded under urethane anesthesia in one whisker barrel field deprived by trimming all contralateral whiskers for 60 days after birth (UD), and in untrimmed controls (CON). In the septal columns around barrels, UD significantly increased the coincident discharge among cortical neurons compared with CON, most notably in layers II/III. In contrast, synchronous discharge was normal between layer IV UD barrel neurons: i.e., not different from CON. Thus, while bilateral whisker deprivation (BD) produced a global deficit in the development of synchrony in layer IV, UD did not block the development of synchrony between neurons in layer IV barrels and increased synchrony within septal circuits. We conclude that changes in synchronous discharge after UD are unexpectedly different from those recorded after BD, and we speculate that this effect may be due to the driven activity from active commissural inputs arising from the contralateral hemisphere that received normal activity levels during postnatal development.

}, keywords = {Animals, Animals, Newborn, Female, Male, Neurons, Physical Stimulation, Rats, Rats, Long-Evans, Sensory Deprivation, Somatosensory Cortex, Touch, Touch Perception, Vibrissae}, issn = {1522-1598}, doi = {10.1152/jn.00562.2013}, author = {Ghoshal, Ayan and Lustig, Brian and Popescu, Maria and Ebner, Ford and Pouget, Pierre} } @article {6124, title = {Ultrasensitive fluorescent proteins for imaging neuronal activity.}, journal = {Nature}, volume = {499}, year = {2013}, month = {2013 Jul 18}, pages = {295-300}, abstract = {

Fluorescent calcium sensors are widely used to image neural activity. Using structure-based mutagenesis and neuron-based screening, we developed a family of ultrasensitive protein calcium sensors (GCaMP6) that outperformed other sensors in cultured neurons and in zebrafish, flies and mice in vivo. In layer 2/3 pyramidal neurons of the mouse visual cortex, GCaMP6 reliably detected single action potentials in neuronal somata and orientation-tuned synaptic calcium transients in individual dendritic spines. The orientation tuning of structurally persistent spines was largely stable over timescales of weeks. Orientation tuning averaged across spine populations predicted the tuning of their parent cell. Although the somata of GABAergic neurons showed little orientation tuning, their dendrites included highly tuned dendritic segments (5{\textendash}40-{\textmu}m long). GCaMP6 sensors thus provide new windows into the organization and dynamics of neural circuits over multiple spatial and temporal scales.

}, doi = {10.1038/nature12354}, author = {Chen, Tsai-Wen and Wardill, Trevor J. and Sun, Yi and Pulvar, Stefan R. and Renninger, Sabine L. and Baohan, Amy and Schreiter, Eric R and Kerr, Rex A and Orger, Michael B. and Jayaraman, Vivek and Looger, Loren L and Svoboda, Karel and Kim, Douglas S.} } @article {6533, title = {Unclosed HIV-1 capsids suggest a curled sheet model of assembly.}, journal = {Journal of Molecular Biology}, volume = {425}, year = {2013}, month = {2013 Jan 9}, pages = {112-23}, abstract = {

The RNA genome of retroviruses is encased within a protein capsid. To gather insight into the assembly and function of this capsid, we used electron cryotomography to image human immunodeficiency virus (HIV) and equine infectious anemia virus (EIAV) particles. While the majority of viral cores appeared closed, a variety of unclosed structures including rolled sheets, extra flaps, and cores with holes in the tip were also seen. Simulations of nonequilibrium growth of elastic sheets recapitulated each of these aberrations and further predicted the occasional presence of seams, for which tentative evidence was also found within the cryotomograms. To test the integrity of viral capsids in vivo, we observed that \ 25\% of cytoplasmic HIV complexes captured by TRIM5α had holes large enough to allow internal green fluorescent protein (GFP) molecules to escape. Together, these findings suggest that HIV assembly at least sometimes involves the union in space of two edges of a curling sheet and results in a substantial number of unclosed forms.

}, keywords = {Animals, Capsid, Carrier Proteins, Computer Simulation, Cryoelectron Microscopy, Equine, Fluorescence, Green Fluorescent Proteins, HEK293 Cells, HIV-1, Humans, Infectious Anemia Virus, Microscopy, Models, Molecular, Viral Core Proteins, Virus Assembly}, issn = {1089-8638}, doi = {10.1016/j.jmb.2012.10.006}, author = {Yu, Zhiheng and Dobro, Megan J and Woodward, Cora L and Levandovsky, Artem and Danielson, Cindy M and Sandrin, Virginie and Shi, Jiong and Aiken, Christopher and Zandi, Roya and Hope, Thomas J and Jensen, Grant J} } @article {6145, title = {Unsupervised segmentation of noisy electron microscopy images using salient watersheds and region merging.}, journal = {BMC Bioinformatics}, volume = {14}, year = {2013}, month = {2013 Oct 4}, pages = {294}, abstract = {

Background: Segmenting electron microscopy (EM) images of cellular and subcellular processes in the nervous system is a key step in many bioimaging pipelines involving classification and labeling of ultrastructures. However, fully automated techniques to segment images are often susceptible to noise and heterogeneity in EM images (e.g. different histological preparations, different organisms, different brain regions, etc.). Supervised techniques to address this problem are often helpful but require large sets of training data, which are often difficult to obtain in practice, especially across many conditions. Results: We propose a new, principled unsupervised algorithm to segment EM images using a two-step approach: edge detection via salient watersheds following by robust region merging. We performed experiments to gather EM neuroimages of two organisms (mouse and fruit fly) using different histological preparations and generated manually curated ground-truth segmentations. We compared our algorithm against several state-of- the-art unsupervised segmentation algorithms and found superior performance using two standard measures of under-and over-segmentation error. Conclusions: Our algorithm is general and may be applicable to other large-scale segmentation problems for bioimages.

}, issn = {1471-2105}, doi = {10.1186/1471-2105-14-294}, author = {Navlakha, Saket and Ahammad, Parvez and Myers, Eugene W}, editor = {Myers, Eugene W} } @article {6302, title = {Ultrabithorax confers spatial identity in a context-specific manner in the Drosophila postembryonic ventral nervous system.}, journal = {Neural Development}, volume = {7}, year = {2012}, month = {2012 Sep 11}, pages = {31}, abstract = {

BACKGROUND: In holometabolous insects such as Drosophila melanogaster, neuroblasts produce an initial population of diverse neurons during embryogenesis and a much larger set of adult-specific neurons during larval life. In the ventral CNS, many of these secondary neuronal lineages differ significantly from one body segment to another, suggesting a role for anteroposterior patterning genes. RESULTS: Here we systematically characterize the expression pattern and function of the Hox gene Ultrabithorax (Ubx) in all 25 postembryonic lineages. We find that Ubx is expressed in a segment-, lineage-, and hemilineage-specific manner in the thoracic and anterior abdominal segments. When Ubx is removed from neuroblasts via mitotic recombination, neurons in these segments exhibit the morphologies and survival patterns of their anterior thoracic counterparts. Conversely, when Ubx is ectopically expressed in anterior thoracic segments, neurons exhibit complementary posterior transformation phenotypes. CONCLUSION: Our findings demonstrate that Ubx plays a critical role in conferring segment-appropriate morphology and survival on individual neurons in the adult-specific ventral CNS. Moreover, while always conferring spatial identity in some sense, Ubx has been co-opted during evolution for distinct and even opposite functions in different neuronal hemilineages.

}, keywords = {Animals, Cell Death, Developmental, Drosophila, Drosophila melanogaster, Drosophila Proteins, Gene Expression Regulation, Genetically Modified, Homeodomain Proteins, Larva, Nervous System, Transcription Factors}, issn = {1749-8104}, doi = {10.1186/1749-8104-7-31}, author = {Marin, Elizabeth C and Dry, Katie E and Alaimo, Danielle R and Rudd, Kirstin T and Cillo, Anthony R and Clenshaw, Michael E and Negre, Nicolas and White, Kevin P and Truman, James W} } @article {46722, title = {An unbiased analysis method to quantify mRNA localization reveals its correlation with cell motility.}, journal = {Cell Reports}, volume = {1}, year = {2012}, month = {2012 Feb 23}, pages = {179-84}, abstract = {

Localization of mRNA is a critical mechanism used by a large fraction of transcripts to restrict its translation to specific cellular regions. Although current high-resolution imaging techniques provide ample information, the analysis methods for localization have either been qualitative or employed quantification in nonrandomly selected regions of interest. Here, we describe an analytical method for objective quantification of mRNA localization using a combination of two characteristics of its molecular distribution, polarization and dispersion. The validity of the method is demonstrated using single-molecule FISH images of budding yeast and fibroblasts. Live-cell analysis of endogenous β-actin mRNA in mouse fibroblasts reveals that mRNA polarization has a half-life of ~16 min and is cross-correlated with directed cell migration. This novel approach provides insights into the dynamic regulation of mRNA localization and its physiological roles.

}, keywords = {Actins, Animals, Cell Movement, Chick Embryo, Computer Simulation, Embryo, Mammalian, Fibroblasts, Green Fluorescent Proteins, Imaging, Three-Dimensional, In Situ Hybridization, Mice, Monte Carlo Method, RNA Transport, RNA, Messenger, Saccharomyces cerevisiae}, issn = {2211-1247}, doi = {10.1016/j.celrep.2011.12.009}, author = {Park, Hye Yoon and Trcek, Tatjana and Wells, Amber L and Chao, Jeffrey A and Singer, Robert H} } @article {4486, title = {Use of a Drosophila genome-wide conserved sequence database to identify functionally related cis-regulatory enhancers.}, journal = {Developmental Dynamics: An Official Publication of the American Association of Anatomists}, volume = {241}, year = {2012}, month = {2012 Jan}, pages = {169-89}, abstract = {

Phylogenetic footprinting has revealed that cis-regulatory enhancers consist of conserved DNA sequence clusters (CSCs). Currently, there is no systematic approach for enhancer discovery and analysis that takes full-advantage of the sequence information within enhancer CSCs.

}, issn = {1097-0177}, doi = {10.1002/dvdy.22728}, author = {Brody, Thomas and Yavatkar, Amarendra S and Kuzin, Alexander and Kundu, Mukta and Tyson, Leonard J and Ross, Jermaine and Lin, Tzu-Yang and Lee, Chi-Hon and Awasaki, Takeshi and Lee, Tzumin and Odenwald, Ward F} } @article {4629, title = {Using translational enhancers to increase transgene expression in Drosophila.}, journal = {Proceedings of the National Academy of Sciences of the United States of America}, volume = {109}, year = {2012}, month = {2012 Apr 9}, pages = {6626-31}, abstract = {

The ability to specify the expression levels of exogenous genes inserted in the genomes of transgenic animals is critical for the success of a wide variety of experimental manipulations. Protein production can be regulated at the level of transcription, mRNA transport, mRNA half-life, or translation efficiency. In this report, we show that several well-characterized sequence elements derived from plant and insect viruses are able to function in Drosophila to increase the apparent translational efficiency of mRNAs by as much as 20-fold. These increases render expression levels sufficient for genetic constructs previously requiring multiple copies to be effective in single copy, including constructs expressing the temperature-sensitive inactivator of neuronal function Shibire(ts1), and for the use of cytoplasmic GFP to image the fine processes of neurons.

}, issn = {1091-6490}, doi = {10.1073/pnas.1204520109}, author = {Pfeiffer, Barret D and Truman, James W and Rubin, Gerald M} } @article {4297, title = {Ultrafast widefield optical sectioning microscopy by multifocal temporal focusing.}, journal = {Optics Express}, volume = {18}, year = {2010}, month = {2010 Sep 13}, pages = {19645-55}, abstract = {

The need for optical sectioning in bio-imaging has amongst others led to the development of the two-photon scanning microscopy. However, this comes with some intrinsic fundamental limitations in the temporal domain as the focused spot has to be scanned mechanically in the sample plane. Hence for a large number of biological applications where imaging speed is a limiting factor, it would be significantly advantageous to generate widefield excitations with an optical sectioning comparable to the two-photon scanning microscopy. Recently by using the technique of temporal focusing it was shown that high axial resolution widefield excitation can be generated in picosecond time scales without any mechanical moving parts. However the achievable axial resolution is still well above that of a two-photon scanning microscope. Here we demonstrate a new ultrafast widefield two-photon imaging technique termed Multifocal Temporal Focusing (MUTEF) which relies on the generation of a set of diffraction limited beams produced by an Echelle grating that scan across a second tilted diffraction grating in picosecond time scale, generating a widefield excitation area with an axial resolution comparable to a two-photon scanning microscope. Using this method we have shown widefield two-photon imaging on fixed biological samples with an axial sectioning with a FWHM of \ 0.85 μm.

}, keywords = {Equipment Design, Equipment Failure Analysis, Fluorescence, Image Enhancement, Lenses, Lighting, Microscopy, Multiphoton, Refractometry, Reproducibility of Results, Sensitivity and Specificity}, issn = {1094-4087}, doi = {10.1364/OE.18.019645}, author = {Vaziri, Alipasha and Shank, Charles V} } @article {1235, title = {Ultrastructural analysis of hippocampal neuropil from the connectomics perspective.}, journal = {Neuron}, volume = {67}, year = {2010}, month = {2010 Sep 23}, pages = {1009-20}, abstract = {

Complete reconstructions of vertebrate neuronal circuits on the synaptic level require new approaches. Here, serial section transmission electron microscopy was automated to densely reconstruct four volumes, totaling 670 μm(3), from the rat hippocampus as proving grounds to determine when axo-dendritic proximities predict synapses. First, in contrast with Peters{\textquoteright} rule, the density of axons within reach of dendritic spines did not predict synaptic density along dendrites because the fraction of axons making synapses was variable. Second, an axo-dendritic touch did not predict a synapse; nevertheless, the density of synapses along a hippocampal dendrite appeared to be a universal fraction, 0.2, of the density of touches. Finally, the largest touch between an axonal bouton and spine indicated the site of actual synapses with about 80\% precision but would miss about half of all synapses. Thus, it will be difficult to predict synaptic connectivity using data sets missing ultrastructural details that distinguish between axo-dendritic touches and bona fide synapses.

}, keywords = {Animals, Automatic Data Processing, Axons, Dendrites, Electron, Hippocampus, Long-Evans, Male, Microscopy, Neuropil, Newborn, Rats, Synapses, Transmission}, issn = {1097-4199}, doi = {10.1371/journal.pcbi.1001066}, author = {Mishchenko, Yuriy and Hu, Tao and Spacek, Josef and Mendenhall, John and Harris, Kristen M and Chklovskii, Dmitri B} } @article {2387, title = {Unexpected roles for core promoter recognition factors in cell-type-specific transcription and gene regulation.}, journal = {Nature Reviews. Genetics}, volume = {11}, year = {2010}, month = {2010 Aug}, pages = {549-58}, abstract = {

The eukaryotic core promoter recognition complex was generally thought to play an essential but passive role in the regulation of gene expression. However, recent evidence now indicates that core promoter recognition complexes together with {\textquoteright}non-prototypical{\textquoteright} subunits may have a vital regulatory function in driving cell-specific programmes of transcription during development. Furthermore, new roles for components of these complexes have been identified beyond development; for example, in mediating interactions with chromatin and in maintaining active gene expression across cell divisions.

}, keywords = {Animals, Cell Differentiation, DNA, Embryonic Development, Female, Genetic, Germ Cells, Humans, Male, Promoter Regions, RNA Polymerase II, Transcription, Transcription Factors, Transcriptional Activation}, issn = {1471-0064}, doi = {10.1073/pnas.1100640108}, author = {Goodrich, James A and Tjian, Robert} } @inbook {2558, title = {Using Drosophila to reveal insight into protein misfolding disease.}, booktitle = {Protein Misfolding Diseases: Current and Emerging Principles and Therapies}, year = {2010}, author = {Bilen, Julide and Bonini, Nancy M}, editor = {Ramirez- Alvarado, M and Kelly, J and Dobson, C} } @conference {6532, title = {Unfolding warping for object recognition.}, booktitle = {19TH International Conference on Pattern Recognition}, year = {2008}, month = {2008 December 11}, publisher = {IEEE}, organization = {IEEE}, address = {Tampa, FL}, abstract = {

In practice, understanding the spatial relationships between the surfaces of an object, can significantly improve the performance of object recognition systems. In this paper we propose a novel framework to recognize objects in pictures taken from arbitrary viewpoints. The idea is to maintain the frontal views of the major faces of objects in a global flat map. Then an unfolding warping technique is used to change the pose of the query object in the test view so that all visible surfaces of the object can be observed from a frontal viewpoint, improving the handling of serious occlusions and large viewpoint changes. We demonstrate the effectiveness of our approach through analysis of recognition trials of complex objects with comparison to popular methods.

}, isbn = {978-1-4244-2174-9}, doi = {10.1109/ICPR.2008.4761188}, author = {Xie, Jun and Hu, Min and Shah, Mubarak} } @article {46303, title = {Universal memory mechanism for familiarity recognition and identification.}, journal = {The Journal of Neuroscience : The Official Journal of the Society for Neuroscience}, volume = {28}, year = {2008}, month = {2008 Jan 2}, pages = {239-48}, abstract = {

Macaque monkeys were tested on a delayed-match-to-multiple-sample task, with either a limited set of well trained images (in randomized sequence) or with never-before-seen images. They performed much better with novel images. False positives were mostly limited to catch-trial image repetitions from the preceding trial. This result implies extremely effective one-shot learning, resembling Standing{\textquoteright}s finding that people detect familiarity for 10,000 once-seen pictures (with 80\% accuracy) (Standing, 1973). Familiarity memory may differ essentially from identification, which embeds and generates contextual information. When encountering another person, we can say immediately whether his or her face is familiar. However, it may be difficult for us to identify the same person. To accompany the psychophysical findings, we present a generic neural network model reproducing these behaviors, based on the same conservative Hebbian synaptic plasticity that generates delay activity identification memory. Familiarity becomes the first step toward establishing identification. Adding an inter-trial reset mechanism limits false positives for previous-trial images. The model, unlike previous proposals, relates repetition-recognition with enhanced neural activity, as recently observed experimentally in 92\% of differential cells in prefrontal cortex, an area directly involved in familiarity recognition. There may be an essential functional difference between enhanced responses to novel versus to familiar images: The maximal signal from temporal cortex is for novel stimuli, facilitating additional sensory processing of newly acquired stimuli. The maximal signal for familiar stimuli arising in prefrontal cortex facilitates the formation of selective delay activity, as well as additional consolidation of the memory of the image in an upstream cortical module.

}, keywords = {Animals, Behavior, Animal, Computer Simulation, Discrimination (Psychology), Haplorhini, Identification (Psychology), Models, Neurological, Neural Networks (Computer), Photic Stimulation, Recognition (Psychology), ROC Curve, Task Performance and Analysis}, issn = {1529-2401}, doi = {10.1523/JNEUROSCI.4799-07.2008}, author = {Yakovlev, Volodya and Amit, Daniel J and Romani, Sandro and Hochstein, Shaul} } @proceedings {3302, title = {Unsupervised discovery of action hierarchies in large collections of activity videos.}, year = {2007}, month = {2007}, abstract = {

Given a large collection of videos containing activities, we investigate the problem of organizing it in an unsupervised fashion into a hierarchy based on the similarity of actions embedded in the videos. We use spatio-temporal volumes of filtered motion vectors to compute appearance-invariant action similarity measures efficiently - and use these similarity measures in hierarchical agglomerative clustering to organize videos into a hierarchy such that neighboring nodes contain similar actions. This naturally leads to a simple automatic scheme for selecting videos of representative actions (exemplars) from the database and for efficiently indexing the whole database. We compute a performance metric on the hierarchical structure to evaluate goodness of the estimated hierarchy, and show that this metric has potential for predicting the clustering performance of various joining criteria used in building hierarchies. Our results show that perceptually meaningful hierarchies can be constructed based on action similarities with minimal user supervision, while providing favorable clustering performance and retrieval performance.

}, author = {Ahammad, Parvez and Yeo, C and Ramchandran, K and Sastry, S} } @conference {2847, title = {Unsupervised learning of boosted tree classifier using graph cuts for hand pose recognition.}, booktitle = {British Machine Vision Conference}, year = {2006}, month = {2006 Sep 4}, author = {Parag, Toufiq and Elgammal, Ahmed} } @article {3938, title = {An unstructured initiation site is required for efficient proteasome-mediated degradation.}, journal = {Nature Structural \& Molecular Biology}, volume = {11}, year = {2004}, month = {2004 Sep}, pages = {830-7}, abstract = {

The proteasome is the main ATP-dependent protease in eukaryotic cells and controls the concentration of many regulatory proteins in the cytosol and nucleus. Proteins are targeted to the proteasome by the covalent attachment of polyubiquitin chains. The ubiquitin modification serves as the proteasome recognition element but by itself is not sufficient for efficient degradation of folded proteins. We report that proteolysis of tightly folded proteins is accelerated greatly when an unstructured region is attached to the substrate. The unstructured region serves as the initiation site for degradation and is hydrolyzed first, after which the rest of the protein is digested sequentially. These results identify the initiation site as a novel component of the targeting signal, which is required to engage the proteasome unfolding machinery efficiently. The proteasome degrades a substrate by first binding to its ubiquitin modification and then initiating unfolding at an unstructured region.

}, keywords = {Adenosine Triphosphate, Animals, Bacillus, Binding Sites, Biological, Catalysis, Cell Nucleus, Cysteine Endopeptidases, Cytosol, Electrophoresis, Endopeptidases, Escherichia coli, Genetic, Hydrolysis, Models, Multienzyme Complexes, Polyacrylamide Gel, Promoter Regions, Proteasome Endopeptidase Complex, Protein Binding, Protein Folding, Protein Structure, Rabbits, Temperature, Tertiary, Time Factors, Ubiquitin}, issn = {1545-9993}, doi = {10.1038/nsmb814}, author = {Prakash, Sumit and Tian, Lin and Ratliff, Kevin S and Lehotzky, Rebecca E and Matouschek, Andreas} } @article {4010, title = {The uncertain response in the bottlenosed dolphin (Tursiops truncatus).}, journal = {Journal of Experimental Psychology}, volume = {124}, year = {1995}, month = {1995 Dec}, pages = {391-408}, abstract = {

Humans respond adaptively to uncertainty by escaping or seeking additional information. To foster a comparative study of uncertainty processes, we asked whether humans and a bottlenosed dolphin (Tursiops truncatus) would use similarly a psychophysical uncertain response. Human observers and the dolphin were given 2 primary discrimination responses and a way to escape chosen trials into easier ones. Humans escaped sparingly from the most difficult trials near threshold that left them demonstrably uncertain of the stimulus. The dolphin performed nearly identically. The behavior of both species is considered from the perspectives of signal detection theory and optimality theory, and its appropriate interpretation is discussed. Human and dolphin uncertain responses seem to be interesting cognitive analogs and may depend on cognitive or controlled decisional mechanisms. The capacity to monitor ongoing cognition, and use uncertainty appropriately, would be a valuable adaptation for animal minds. This recommends uncertainty processes as an important but neglected area for future comparative research.

}, keywords = {Animal, Animals, Auditory Threshold, Behavior, Biological, Cognition, Discrimination (Psychology), Humans, Kinetics, Models, Probability, Psychiatric Status Rating Scales, Reinforcement (Psychology), Task Performance and Analysis}, issn = {0096-3445}, author = {Smith, J D and Schull, J and Strote, J and McGee, K and Egnor, R and Erb, L} }