@article {69745, title = {Encoding of cerebellar dentate neuron activity during visual attention in rhesus macaques.}, journal = {Elife}, volume = {13}, year = {2025}, month = {2025 Jan 16}, abstract = {

The role of cerebellum in controlling eye movements is well established, but its contribution to more complex forms of visual behavior has remained elusive. To study cerebellar activity during visual attention we recorded extracellular activity of dentate nucleus (DN) neurons in two non-human primates (NHPs). NHPs were trained to read the direction indicated by a peripheral visual stimulus while maintaining fixation at the center, and report the direction of the cue by performing a saccadic eye movement into the same direction following a delay. We found that single-unit DN neurons modulated spiking activity over the entire time course of the task, and that their activity often bridged temporally separated intra-trial events, yet in a heterogeneous manner. To better understand the heterogeneous relationship between task structure, behavioral performance, and neural dynamics, we constructed a behavioral, an encoding, and a decoding model. Both NHPs showed different behavioral strategies, which influenced the performance. Activity of the DN neurons reflected the unique strategies, with the direction of the visual stimulus frequently being encoded long before an upcoming saccade. Moreover, the latency of the ramping activity of DN neurons following presentation of the visual stimulus was shorter in the better performing NHP. Labeling with the retrograde tracer Cholera Toxin B in the recording location in the DN indicated that these neurons predominantly receive inputs from Purkinje cells in the D1 and D2 zones of the lateral cerebellum as well as neurons of the principal olive and medial pons, all regions known to connect with neurons in the prefrontal cortex contributing to planning of saccades. Together, our results highlight that DN neurons can dynamically modulate their activity during a visual attention task, comprising not only sensorimotor but also cognitive attentional components.

}, keywords = {Animals, Attention, Cerebellar Nuclei, Macaca mulatta, Male, Neurons, Photic Stimulation, Saccades, Visual Perception}, issn = {2050-084X}, doi = {10.7554/eLife.99696}, author = {Flierman, Nico A and Koay, Sue Ann and van Hoogstraten, Willem S and Ruigrok, Tom J H and Roelfsema, Pieter and Badura, Aleksandra and De Zeeuw, Chris I} } @article {69544, title = {Encoding of cerebellar dentate neuronal activity during visual attention in rhesus macaques}, journal = {bioRxiv}, year = {2024}, month = {2024 Jul 20}, abstract = {

The role of cerebellum in controlling eye movements is well established, but its contribution to more complex forms of visual behavior has remained elusive. To study cerebellar activity during visual attention we recorded extracellular activity of dentate nucleus (DN) neurons in two non-human primates (NHPs). NHPs were trained to read the direction indicated by a peripheral visual stimulus while maintaining fixation at the center, and report the direction of the cue by performing a saccadic eye movement into the same direction following a delay. We found that single unit DN neurons modulated spiking activity over the entire time-course of the task, and that their activity often bridged temporally separated intra-trial events, yet in a heterogeneous manner. To better understand the heterogeneous relationship between task structure, behavioral performance and neural dynamics, we constructed a behavioral, an encoding and a decoding model. Both NHPs showed different behavioral strategies, which influenced the performance. Activity of the DN neurons reflected the unique strategies, with the direction of the visual stimulus frequently being encoded long before an upcoming saccade. Retrograde labeling of the recording location indicated that these neurons receive predominantly inputs from Purkinje cells in the lateral cerebellum as well as neurons of the principal olive and medial pons, all regions known to connect with neurons in the prefrontal cortex contributing to planning of saccades. Together, our results highlight that DN neurons can dynamically modulate their activity during a visual attention task, comprising not only sensorimotor but also cognitive attentional components.

}, doi = {10.1101/2024.07.18.604119}, url = {https://www.doi.org/10.1101/2024.07.18.604119}, author = {Flierman, Nico A. and Koay, Sue Ann and van Hoogstraten, Willem S. and Ruigrok, Tom J.H. and Roelfsema, Pieter R. and Badura, Aleksandra and De Zeeuw, Chris I.} } @article {67280, title = {CaImAn an open source tool for scalable calcium imaging data analysis}, journal = {eLife}, volume = {8}, year = {2019}, month = {01/2019}, abstract = {

Advances in fluorescence microscopy enable monitoring larger brain areas in-vivo with finer time resolution. The resulting data rates require reproducible analysis pipelines that are reliable, fully automated, and scalable to datasets generated over the course of months. We present CaImAn, an open-source library for calcium imaging data analysis. CaImAn\ provides automatic and scalable methods to address problems common to pre-processing, including motion correction, neural activity identification, and registration across different sessions of data collection. It does this while requiring minimal user intervention, with good scalability on computers ranging from laptops to high-performance computing clusters. CaImAn\ is suitable for two-photon and one-photon imaging, and also enables real-time analysis on streaming data. To benchmark the performance of CaImAn\ we collected and combined a corpus of manual annotations from multiple labelers on nine mouse two-photon datasets. We demonstrate that CaImAn\ achieves near-human performance in detecting locations of active neurons

}, doi = {10.7554/eLife.38173}, url = {https://elifesciences.org/articles/38173}, author = {Giovannucci, Andrea and Friedrich, Johannes and Gunn, Pat and Kalfon, J{\'e}r{\'e}mie and Brown, Brandon L and Koay, Sue Ann and Taxidis, Jiannis and Najafi, Farzaneh and Gauthier, Jeffrey L and Zhou, Pengcheng and Khakh, Baljit S and Tank, David W and Chklovskii, Dmitri B and Pnevmatikakis, Eftychios A} } @conference {67294, title = {Neural Correlates of Cognition in Primary Visual versus Downstream Posterior Cortices During Evidence Accumulation}, booktitle = {APS March Meeting Abstracts}, year = {2019}, month = {01/2019}, abstract = {

The ability of animals to accumulate sensory information across time is fundamental to decision-making. Using a mouse behavioral paradigm where navigational decisions are based on accumulating pulses of visual cues, I compared neural activity in primary visual (V1) to secondary visual and retrosplenial cortices. Even in V1, only a small fraction of neurons had sensory-like responses to cues. Instead, all areas were grossly similar in how neural populations contained a large variety of task-related information from sensory to cognitive, including cue timings, accumulated counts, place/time, decision and reward outcome. Across-trial influences were prevalent, possibly relevant to how animal behavior incorporates past contexts. Intriguingly, all these variables also modulated the amplitudes of sensory responses. While previous work often modeled the accumulation process as integration, the observed scaling of sensory responses by accumulated counts instead suggests a recursive process where sensory responses are gradually amplified. I show that such a multiplicative feedback-loop algorithm better explains psychophysical data than integration, particularly in how the performance transitions into following Weber-Fechner{\textquoteright}s Law only at high counts.

}, url = {https://ui.adsabs.harvard.edu/abs/2019APS..MARP67013K/abstract}, author = {Koay, Sue Ann and Tank, David and Brody, Carlos} } @article {67287, title = {Neural Correlates of Cognition in Primary Visual versus Neighboring Posterior Cortices during Visual Evidence-Accumulation-based Navigation}, journal = {bioRxiv}, year = {2019}, month = {03/2019}, abstract = {

Studies of perceptual decision-making have often assumed that the main role of sensory cortices is to provide sensory input to downstream processes that accumulate and drive behavioral decisions. We performed a systematic comparison of neural activity in primary visual (V1) to secondary visual and retrosplenial cortices, as mice performed a task where they should accumulate pulsatile visual cues through time to inform a navigational decision. Even in V1, only a small fraction of neurons had sensory-like responses to cues. Instead, in all areas neurons were sequentially active, and contained information ranging from sensory to cognitive, including cue timings, evidence, place/time, decision and reward outcome. Per-cue sensory responses were amplitude-modulated by various cognitive quantities, notably accumulated evidence. This inspired a multiplicative feedback-loop circuit hypothesis that proposes a more intricate role of sensory areas in the accumulation process, and furthermore explains a surprising observation that perceptual discrimination deviates from Weber-Fechner Law.Highlights / eTOC BlurbMice made navigational decisions based on accumulating pulsatile visual cuesThe bulk of neural activity in visual cortices was sequential and beyond-sensoryAccumulated pulse-counts modulated sensory (cue) responses, suggesting feedbackA feedback-loop neural circuit explains behavioral deviations from Weber{\textquoteright}s LawHighlights / eTOC BlurbIn a task where navigation was informed by accumulated pulsatile visual evidence, neural activity in visual cortices predominantly coded for cognitive variables across multiple timescales, including outside of a visual processing context. Even sensory responses to visual pulses were amplitude-modulated by accumulated pulse counts and other variables, inspiring a multiplicative feedback-loop circuit hypothesis that in turn explained behavioral deviations from Weber-Fechner Law.

}, doi = {10.1101/568766}, url = {https://www.biorxiv.org/content/early/2019/03/06/568766}, author = {Koay, Sue Ann and Thiberge, Stephan Y. and Brody, Carlos D. and Tank, David W.} } @article {67290, title = {Sequential and efficient neural-population coding of complex task information}, journal = {bioRxiv}, year = {2019}, month = {10/2019}, abstract = {

Recent work has highlighted that many types of variables are represented in each neocortical area. How can these many neural representations be organized together without interference, and coherently maintained/updated through time? We recorded from large neural populations in posterior cortices as mice performed a complex, dynamic task involving multiple interrelated variables. The neural encoding implied that correlated task variables were represented by uncorrelated modes in an information-coding subspace. We show via theory that this can enable optimal decoding directions to be insensitive to neural noise levels. Across posterior cortex, principles of efficient coding thus applied to task-specific information, with neural-population modes as the encoding unit. Remarkably, this encoding function was multiplexed with rapidly changing, sequential neural dynamics, yet reliably followed slow changes in task-variable correlations through time. We can explain this as due to a mathematical property of high-dimensional spaces that the brain might exploit as a temporal scaffold.

}, doi = {10.1101/801654}, url = {https://www.biorxiv.org/content/early/2019/10/13/801654}, author = {Koay, Sue Ann and Thiberge, Stephan Y. and Brody, Carlos D. and Tank, David W.} } @article {67281, title = {Specialized coding of sensory, motor and cognitive variables in VTA dopamine neurons}, journal = {Nature}, volume = {570}, year = {2019}, month = {05/2019}, pages = {509 - 513}, abstract = {

There is increased appreciation that dopamine neurons in the midbrain respond not only to reward1\ and reward-predicting cues1,2, but also to other variables such as the distance to reward3, movements4,5,6,7,8,9\ and behavioural choices10,11. An important question is how the responses to these diverse variables are organized across the population of dopamine neurons. Whether individual dopamine neurons multiplex several variables, or whether there are subsets of neurons that are specialized in encoding specific behavioural variables remains unclear. This fundamental question has been difficult to resolve because recordings from large populations of individual dopamine neurons have not been performed in a behavioural task with sufficient complexity to examine these diverse variables simultaneously. Here, to address this gap, we used two-photon calcium imaging through an implanted lens to record the activity of more than 300 dopamine neurons from the ventral tegmental area of the mouse midbrain during a complex decision-making task. As mice navigated in a virtual-reality environment, dopamine neurons encoded an array of sensory, motor and cognitive variables. These responses were functionally clustered, such that subpopulations of neurons transmitted information about a subset of behavioural variables, in addition to encoding reward. These functional clusters were spatially organized, with neighbouring neurons more likely to be part of the same cluster. Together with the topography between dopamine neurons and their projections, this specialization and anatomical organization may aid downstream circuits in correctly interpreting the wide range of signals transmitted by dopamine neurons.

}, issn = {0028-0836}, doi = {10.1038/s41586-019-1261-9}, url = {http://www.nature.com/articles/s41586-019-1261-9}, author = {Engelhard, Ben and Finkelstein, Joel and Cox, Julia and Fleming, Weston and Jang, Hee Jae and Ornelas, Sharon and Koay, Sue Ann and Thiberge, Stephan Y. and Daw, Nathaniel D. and Tank, David W. and Witten, Ilana B.} } @article {67289, title = {CalmAn: An open source tool for scalable Calcium Imaging data Analysis}, journal = {bioRxiv}, year = {2018}, month = {06/2018}, abstract = {

Advances in fluorescence microscopy enable monitoring larger brain areas in-vivo with finer time resolution. The resulting data rates require reproducible analysis pipelines that are reliable, fully automated, and scalable to datasets generated over the course of months. Here we present CaImAn, an open-source library for calcium imaging data analysis. CaImAn provides automatic and scalable methods to address problems common to pre-processing, including motion correction, neural activity identification, and registration across different sessions of data collection. It does this while requiring minimal user intervention, with good performance on computers ranging from laptops to high-performance computing clusters. CaImAn is suitable for two-photon and one-photon imaging, and also enables real-time analysis on streaming data. To benchmark the performance of CaImAn we collected a corpus of ground truth annotations from multiple labelers on nine mouse two-photon datasets. We demonstrate that CaImAn achieves near-human performance in detecting locations of active neurons.

}, doi = {10.1101/339564}, url = {https://www.biorxiv.org/content/early/2018/06/05/339564}, author = {Giovannucci, Andrea and Friedrich, Johannes and Gunn, Pat and Kalfon, J{\'e}r{\'e}mie and Koay, Sue Ann and Taxidis, Jiannis and Najafi, Farzaneh and Gauthier, Jeffrey L. and Zhou, Pengcheng and Tank, David W. and Chklovskii, Dmitri and Pnevmatikakis, Eftychios A.} } @article {67284, title = {Cerebellar involvement in an evidence-accumulation decision-making task}, journal = {eLife}, volume = {7}, year = {2018}, month = {08/2018}, abstract = {

To make successful evidence-based decisions, the brain must rapidly and accurately transform sensory inputs into specific goal-directed behaviors. Most experimental work on this subject has focused on forebrain mechanisms. Using a novel evidence-accumulation task for mice, we performed recording and perturbation studies of crus I of the lateral posterior cerebellum, which communicates bidirectionally with numerous forebrain regions. Cerebellar inactivation led to a reduction in the fraction of correct trials. Using two-photon fluorescence imaging of calcium, we found that Purkinje cell somatic activity contained choice/evidence-related information. Decision errors were represented by dendritic calcium spikes, which in other contexts are known to drive cerebellar plasticity. We propose that cerebellar circuitry may contribute to computations that support accurate performance in this perceptual decision-making task.

}, doi = {10.7554/eLife.36781}, url = {https://elifesciences.org/articles/36781}, author = {Deverett, Ben and Koay, Sue Ann and Oostland, Marlies and Wang, Samuel S-H} } @article {67292, title = {A cerebellar role in evidence-guided decision-making}, journal = {bioRxiv}, year = {2018}, month = {06/2018}, abstract = {

To make successful evidence-based decisions, the brain must rapidly and accurately transform sensory inputs into specific goal-directed behaviors. Most experimental work on this subject has focused on forebrain mechanisms. Here we show that during perceptual decision-making over a period of seconds, decision-, sensory-, and error-related information converge on the lateral posterior cerebellum in crus I, a structure that communicates bidirectionally with numerous forebrain regions. We trained mice on a novel evidence-accumulation task and demonstrated that cerebellar inactivation reduces behavioral accuracy without impairing motor parameters of action. Using two-photon calcium imaging, we found that Purkinje cell somatic activity encoded choice- and evidence-related variables. Decision errors were represented by dendritic calcium spikes, which are known to drive plasticity. We propose that cerebellar circuitry may contribute to the set of distributed computations in the brain that support accurate perceptual decision-making.

}, doi = {10.1101/343095}, url = {https://www.biorxiv.org/content/early/2018/06/11/343095}, author = {Deverett, Ben and Koay, Sue Ann and Oostland, Marlies and Wang, Samuel S.-H.} } @article {67291, title = {Detecting and Correcting False Transients in Calcium Imaging}, journal = {bioRxiv}, year = {2018}, month = {11/2018}, abstract = {

Population recordings of calcium activity are a major source of insight into neural function. Large dataset sizes often require automated methods, but automation can introduce errors that are difficult to detect. Here we show that automatic time course estimation can sometimes lead to significant misattribution errors, in which fluorescence is ascribed to the wrong cell. Misattribution arises when the shapes of overlapping cells are imperfectly defined, or when entire cells or processes are not identified, and misattribution can even be produced by methods specifically designed to handle overlap. To diagnose this problem, we develop a transient-by-transient metric and a visualization tool that allow users to quickly assess the degree of misattribution in large populations. To filter out misattribution, we also design a robust estimator that explicitly accounts for contaminating signals in a generative model. Our methods can be combined with essentially any cell finding technique, empowering users to diagnose and correct at large scale a problem that has the potential to significantly alter scientific conclusions.

}, doi = {10.1101/473470}, url = {https://www.biorxiv.org/content/early/2018/11/19/473470}, author = {Gauthier, Jeff L. and Koay, Sue Ann and Nieh, Edward H. and Tank, David W. and Pillow, Jonathan W. and Charles, Adam S.} } @article {67288, title = {Specialized and spatially organized coding of sensory, motor, and cognitive variables in midbrain dopamine neurons}, journal = {bioRxiv}, year = {2018}, month = {10/2018}, abstract = {

There is increased appreciation that dopamine (DA) neurons in the midbrain respond not only to reward 1,2 and reward-predicting cues 1,3,4, but also to other variables such as distance to reward 5, movements 6{\textendash}11 and behavioral choices 12{\textendash}15. Based on these findings, a major open question is how the responses to these diverse variables are organized across the population of DA neurons. In other words, do individual DA neurons multiplex multiple variables, or are subsets of neurons specialized in encoding specific behavioral variables? The reason that this fundamental question has been difficult to resolve is that recordings from large populations of individual DA neurons have not been performed in a behavioral task with sufficient complexity to examine these diverse variables simultaneously. To address this gap, we used 2-photon calcium imaging through an implanted lens to record activity of \>300 midbrain DA neurons in the VTA during a complex decision-making task. As mice navigated in a virtual reality (VR) environment, DA neurons encoded an array of sensory, motor, and cognitive variables. These responses were functionally clustered, such that subpopulations of neurons transmitted information about a subset of behavioral variables, in addition to encoding reward. These functional clusters were spatially organized, such that neighboring neurons were more likely to be part of the same cluster. Taken together with the topography between DA neurons and their projections, this specialization and anatomical organization may aid downstream circuits in correctly interpreting the wide range of signals transmitted by DA neurons.

}, doi = {10.1101/456194}, url = {https://www.biorxiv.org/content/early/2018/10/29/456194}, author = {Engelhard, Ben and Finkelstein, Joel and Cox, Julia and Fleming, Weston and Jang, Hee Jae and Ornelas, Sharon and Koay, Sue Ann and Thiberge, Stephan and Daw, Nathaniel and Tank, David W. and Witten, Ilana B.} } @article {67286, title = {Predictive Coding of Novel versus Familiar Stimuli in the Primary Visual Cortex}, journal = {bioRxiv}, year = {2017}, month = {10/2017}, abstract = {

To explore theories of predictive coding, we presented mice with repeated sequences of images with novel images sparsely substituted. Under these conditions, mice could be rapidly trained to lick in response to a novel image, demonstrating a high level of performance on the first day of testing. Using 2-photon calcium imaging to record from layer 2/3 neurons in the primary visual cortex, we found that novel images evoked excess activity in the majority of neurons. When a new stimulus sequence was repeatedly presented, a majority of neurons had similarly elevated activity for the first few presentations, which then decayed to almost zero activity. The decay time of these transient responses was not fixed, but instead scaled with the length of the stimulus sequence. However, at the same time, we also found a small fraction of the neurons within the population (\~2\%) that continued to respond strongly and periodically to the repeated stimulus. Decoding analysis demonstrated that both the transient and sustained responses encoded information about stimulus identity. We conclude that the layer 2/3 population uses a two-channel predictive code: a dense transient code for novel stimuli and a sparse sustained code for familiar stimuli. These results extend and unify existing theories about the nature of predictive neural codes.

}, doi = {10.1101/197608}, url = {https://www.biorxiv.org/content/early/2017/10/03/197608}, author = {Homann, Jan and Koay, Sue Ann and Glidden, Alistair M. and Tank, David W. and Berry, Michael J.} } @conference {67293, title = {Stochastic filtering of two-photon imaging using reweighted l1}, booktitle = {2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)}, year = {2017}, month = {03/2017}, publisher = {IEEE}, organization = {IEEE}, address = {New Orleans, LA}, abstract = {
Two-photon (TP) calcium imaging is an important imaging modality in neuroscience, allowing for large-scale recording of neural activity in awake, behaving animals at behavior-relevant timescales. Interpretation of TP data requires the accurate extraction of temporal neural activity traces, which can be accomplished via manual or automated methods. In this work we seek to improve the accuracy of both manual and automated TP microscopy demixing methods by introducing a denoising algorithm based on a statistical model of TP data which includes spatial contiguity, sparse activity and Poisson observations. Our method leverages recent developments in stochastic filtering of structured signals based on Laplacian-scale mixture models (LSMs) to model the neural activity in TP data as a set of spatially correlated sparse variables. We apply our method on TP images taken from the visual cortex of an awake, behaving mouse, and demonstrate improved neural activity demixing over current pre-processing techniques.
}, doi = {10.1109/ICASSP.2017.7952314}, url = {https://ieeexplore.ieee.org/abstract/document/7952314}, author = {Charles, Adam S. and Song, Alexander and Koay, Sue Ann and Tank, David W. and Pillow, Jonathan W.} } @article {67282, title = {Volumetric two-photon imaging of neurons using stereoscopy (vTwINS)}, journal = {Nature Methods}, volume = {14}, year = {2017}, month = {03/2017}, pages = {420 - 426}, abstract = {

Two-photon laser scanning microscopy of calcium dynamics using fluorescent indicators is a widely used imaging method for large-scale recording of neural activity\ in vivo. Here, we introduce volumetric two-photon imaging of neurons using stereoscopy (vTwINS), a volumetric calcium imaging method that uses an elongated, V-shaped point spread function to image a 3D brain volume. Single neurons project to spatially displaced {\textquoteright}image pairs{\textquoteright} in the resulting 2D image, and the separation distance between projections is proportional to depth in the volume. To demix the fluorescence time series of individual neurons, we introduce a modified orthogonal matching pursuit algorithm that also infers source locations within the 3D volume. We illustrated vTwINS by imaging neural population activity in the mouse primary visual cortex and hippocampus. Our results demonstrated that vTwINS provides an effective method for volumetric two-photon calcium imaging that increases the number of neurons recorded while maintaining a high frame rate.

}, issn = {1548-7091}, doi = {10.1038/nmeth.4226}, url = {http://www.nature.com/articles/nmeth.4226http://www.nature.com/articles/nmeth.4226.pdfhttp://www.nature.com/articles/nmeth.4226.pdfhttp://www.nature.com/articles/nmeth.4226}, author = {Song, Alexander and Charles, Adam S and Koay, Sue Ann and Gauthier, Jeff L and Thiberge, Stephan Y and Pillow, Jonathan W and Tank, David W} } @article {67279, title = {Simplified models for LHC new physics searches}, journal = {Journal of Physics G: Nuclear and Particle Physics}, volume = {39}, year = {2012}, month = {Jan-10-2012}, pages = {105005}, abstract = {

This document proposes a collection of simplified models relevant to the design of new-physics searches at the Large Hadron Collider (LHC) and the characterization of their results. Both ATLAS and CMS have already presented some results in terms of simplified models, and we encourage them to continue and expand this effort, which supplements both signature-based results and benchmark model interpretations. A simplified model is defined by an effective Lagrangian describing the interactions of a small number of new particles. Simplified models can equally well be described by a small number of masses and cross-sections. These parameters are directly related to collider physics observables, making simplified models a particularly effective framework for evaluating searches and a useful starting point for characterizing positive signals of new physics. This document serves as an official summary of the results from the {\textquoteright}Topologies for Early LHC Searches{\textquoteright} workshop, held at SLAC in September of 2010, the purpose of which was to develop a set of representative models that can be used to cover all relevant phase space in experimental searches. Particular emphasis is placed on searches relevant for the first ~50{\textendash}500 pb-1\ of data and those motivated by supersymmetric models. This note largely summarizes material posted at\ http://lhcnewphysics.org/, which includes simplified model definitions, Monte Carlo material, and supporting contacts within the theory community. We also comment on future developments that may be useful as more data is gathered and analyzed by the experiments.

}, issn = {0954-3899}, doi = {10.1088/0954-3899/39/10/105005}, url = {https://iopscience.iop.org/article/10.1088/0954-3899/39/10/105005}, author = {Alves, Daniele and Arkani-Hamed, Nima and Arora, Sanjay and Bai, Yang and Baumgart, Matthew and Berger, Joshua and Buckley, Matthew and Butler, Bart and Chang, Spencer and Cheng, Hsin-Chia and Cheung, Clifford and Chivukula, R Sekhar and Cho, Won Sang and Cotta, Randy and D{\textquoteright}Alfonso, Mariarosaria and Hedri, Sonia El and Essig, Rouven and Evans, Jared A and Fitzpatrick, Liam and Fox, Patrick and Franceschini, Roberto and Freitas, Ayres and Gainer, James S and Gershtein, Yuri and Gray, Richard and Gregoire, Thomas and Gripaios, Ben and Gunion, Jack and Han, Tao and Haas, Andy and Hansson, Per and Hewett, JoAnne and Hits, Dmitry and Hubisz, Jay and Izaguirre, Eder and Kaplan, Jared and Katz, Emanuel and Kilic, Can and Kim, Hyung-Do and Kitano, Ryuichiro and Koay, Sue Ann and Ko, Pyungwon and Krohn, David and Kuflik, Eric and Lewis, Ian and Lisanti, Mariangela and Liu, Tao and Liu, Zhen and Lu, Ran and Luty, Markus and Meade, Patrick and Morrissey, David and Mrenna, Stephen and Nojiri, Mihoko and Okui, Takemichi and Padhi, Sanjay and Papucci, Michele and Park, Michael and Park, Myeonghun and Perelstein, Maxim and Peskin, Michael and Phalen, Daniel and Rehermann, Keith and Rentala, Vikram and Roy, Tuhin and Ruderman, Joshua T and Sanz, Veronica and Schmaltz, Martin and Schnetzer, Stephen and Schuster, Philip and Schwaller, Pedro and Schwartz, Matthew D and Schwartzman, Ariel and Shao, Jing and Shelton, Jessie and Shih, David and Shu, Jing and Silverstein, Daniel and Simmons, Elizabeth and Somalwar, Sunil and Spannowsky, Michael and Spethmann, Christian and Strassler, Matthew and Su, Shufang and Tait, Tim and Thomas, Brooks and Thomas, Scott and Toro, Natalia and Volansky, Tomer and Wacker, Jay and Waltenberger, Wolfgang and Yavin, Itay and Yu, Felix and Zhao, Yue and Zurek, Kathryn} }