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Results 21 through 40 out of 14598

in category neuroscience


21: High-performance GFP-based calcium indicators for imaging activity in neuronal populations and microcompartments

Hod Dana, Yi Sun et al.

11,201 downloads (posted 03 Oct 2018)

Calcium imaging with genetically encoded calcium indicators (GECIs) is routinely used to measure neural activity in intact nervous systems. GECIs are frequently used in one of two different modes: to track activity in large populations of neuronal cell bodies, or to follow dynamics in subcellular compartments such as axons, dendrites and individual synaptic compartments. Despite major advances, calcium imaging is still limited by the biophysical properties of existing GECIs, including affinity, signal-to-noise ratio, rise and decay kinetics, and dynamic range. Using structure-guided mutagenesis and neuron-based screening, we optimized the green fluorescent protein-based GECI GCaMP6 for different modes of in vivo imaging. The jGCaMP7 sensors provide improved detection of individual spikes (jGCaMP7s,f), imaging in neurites and neuropil (jGCaMP7b), and tracking large populations of neurons using 2-photon (jGCaMP7s,f) or wide-field (jGCaMP7c) imaging.


22: A suite of transgenic driver and reporter mouse lines with enhanced brain cell type targeting and functionality

L. Daigle Tanya, Linda Madisen et al.

10,757 downloads (posted 25 Nov 2017)

Modern genetic approaches are powerful in providing access to diverse types of neurons within the mammalian brain and greatly facilitating the study of their function. We here report a large set of driver and reporter transgenic mouse lines, including 23 new driver lines targeting a variety of cortical and subcortical cell populations and 26 new reporter lines expressing an array of molecular tools. In particular, we describe the TIGRE2.0 transgenic platform and introduce Cre-dependent reporter lines that enable optical...


23: Bright and photostable chemigenetic indicators for extended in vivo voltage imaging

Ahmed S. Abdelfattah, Takashi Kawashima et al.

10,561 downloads (posted 06 Oct 2018)

Imaging changes in membrane potential using genetically encoded fluorescent voltage indicators (GEVIs) has great potential for monitoring neuronal activity with high spatial and temporal resolution. Brightness and photostability of fluorescent proteins and rhodopsins have limited the utility of existing GEVIs. We engineered a novel GEVI, Voltron, that utilizes bright and photostable synthetic dyes instead of protein-based fluorophores, extending the combined duration of imaging and number of neurons imaged simultaneousl...


24: Widespread and targeted gene expression by systemic AAV vectors: Production, purification, and administration

Rosemary C Challis, Sripriya Ravindra Kumar et al.

9,839 downloads (posted 11 Jan 2018)

We recently developed novel AAV capsids for efficient and noninvasive gene transfer across the central and peripheral nervous systems. In this protocol, we describe how to produce and systemically administer AAV-PHP viruses to label and/or genetically manipulate cells in the mouse nervous system and organs including the heart. The procedure comprises three separate stages: AAV production, intravenous delivery, and evaluation of transgene expression. The protocol spans eight days, excluding the time required to assess ge...


25: Kilosort: realtime spike-sorting for extracellular electrophysiology with hundreds of channels

Marius Pachitariu, Nicholas Steinmetz et al.

9,797 downloads (posted 30 Jun 2016)

Advances in silicon probe technology mean that in vivo electrophysiological recordings from hundreds of channels will soon become commonplace. To interpret these recordings we need fast, scalable and accurate methods for spike sorting, whose output requires minimal time for manual curation. Here we introduce Kilosort, a spike sorting framework that meets these criteria, and show that it allows rapid and accurate sorting of large-scale in vivo data. Kilosort models the recorded voltage as a sum of template waveforms trig...


26: Molecular architecture of the mouse nervous system

Amit Zeisel, Hannah Hochgerner et al.

9,652 downloads (posted 05 Apr 2018)

The mammalian nervous system executes complex behaviors controlled by specialised, precisely positioned and interacting cell types. Here, we used RNA sequencing of half a million single cells to create a detailed census of cell types in the mouse nervous system. We mapped cell types spatially and derived a hierarchical, data-driven taxonomy. Neurons were the most diverse, and were grouped by developmental anatomical units, and by the expression of neurotransmitters and neuropeptides. Neuronal diversity was driven by gen...


27: A Single-Cell Atlas of Cell Types, States, and Other Transcriptional Patterns from Nine Regions of the Adult Mouse Brain

Arpiar Saunders, Evan Macosko et al.

9,577 downloads (posted 10 Apr 2018)

The mammalian brain is composed of diverse, specialized cell populations, few of which we fully understand. To more systematically ascertain and learn from cellular specializations in the brain, we used Drop-seq to perform single-cell RNA sequencing of 690,000 cells sampled from nine regions of the adult mouse brain: frontal and posterior cortex (156,000 and 99,000 cells, respectively), hippocampus (113,000), thalamus (89,000), cerebellum (26,000), and all of the basal ganglia - the striatum (77,000), globus pallidus ex...


28: The "sewing machine" for minimally invasive neural recording

Timothy L Hanson, Camilo A Diaz-Botia et al.

9,445 downloads (posted 14 Mar 2019)

We present a system for scalable and customizable recording and stimulation of neural activity. In large animals and humans, the current benchmark for high spatial and temporal resolution neural interfaces are fixed arrays of wire or silicon electrodes inserted into the parenchyma of the brain. However, probes that are large and stiff enough to penetrate the brain have been shown to cause acute and chronic damage and inflammation, which limits their longevity, stability, and yield. One approach to this problem is to sep...


29: Nested oscillatory dynamics in cortical organoids model early human brain network development

Cleber A. Trujillo, Richard Gao et al.

9,100 downloads (posted 29 Jun 2018)

Structural and transcriptional changes during early brain maturation follow fixed developmental programs defined by genetics. However, whether this is true for functional network activity remains unknown, primarily due to experimental inaccessibility of the initial stages of the living human brain. Here, we analyzed cortical organoids that spontaneously developed periodic and regular oscillatory network events that are dependent on glutamatergic and GABAergic signaling. These nested oscillations exhibit cross-frequency ...


30: Automated Reconstruction of a Serial-Section EM Drosophila Brain with Flood-Filling Networks and Local Realignment

Peter H. Li, Larry F. Lindsey et al.

9,058 downloads (posted 11 Apr 2019)

Reconstruction of neural circuitry at single-synapse resolution is an attractive target for improving understanding of the nervous system in health and disease. Serial section transmission electron microscopy (ssTEM) is among the most prolific imaging methods employed in pursuit of such reconstructions. We demonstrate how Flood-Filling Networks (FFNs) can be used to computationally segment a forty-teravoxel whole-brain Drosophila ssTEM volume. To compensate for data irregularities and imperfect global alignment, FFNs we...


31: A Connectome of the Adult Drosophila Central Brain

C. Shan Xu, Michal Januszewski et al.

8,768 downloads (posted 21 Jan 2020)

The neural circuits responsible for behavior remain largely unknown. Previous efforts have reconstructed the complete circuits of small animals, with hundreds of neurons, and selected circuits for larger animals. Here we (the FlyEM project at Janelia and collaborators at Google) summarize new methods and present the complete circuitry of a large fraction of the brain of a much more complex animal, the fruit fly Drosophila melanogaster. Improved methods include new procedures to prepare, image, align, segment, find synap...


32: High-dimensional geometry of population responses in visual cortex

Carsen Stringer, Marius Pachitariu et al.

8,559 downloads (posted 22 Jul 2018)

A neuronal population encodes information most efficiently when its activity is uncorrelated and high-dimensional, and most robustly when its activity is correlated and lower-dimensional. Here, we analyzed the correlation structure of natural image coding, in large visual cortical populations recorded from awake mice. Evoked population activity was high dimensional, with correlations obeying an unexpected power-law: the n-th principal component variance scaled as 1/n. This was not inherited from the 1/f spectrum of natu...


33: A neural algorithm for a fundamental computing problem

Sanjoy Dasgupta, Charles F Stevens et al.

8,405 downloads (posted 25 Aug 2017)

Similarity search, such as identifying similar images in a database or similar documents on the Web, is a fundamental computing problem faced by many large-scale information retrieval systems. We discovered that the fly's olfactory circuit solves this problem using a novel variant of a traditional computer science algorithm (called locality-sensitive hashing). The fly's circuit assigns similar neural activity patterns to similar input stimuli (odors), so that behaviors learned from one odor can be applied when a similar...


34: A computational toolbox and step-by-step tutorial for the analysis of neuronal population dynamics in calcium imaging data

Sebastián A. Romano, Verónica Pérez-Schuster et al.

8,183 downloads (posted 28 Jan 2017)

The development of new imaging and optogenetics techniques to study the dynamics of large neuronal circuits is generating datasets of unprecedented volume and complexity, demanding the development of appropriate analysis tools. We present a tutorial for the use of a comprehensive computational toolbox for the analysis of neuronal population activity imaging. It consists of tools for image pre-processing and segmentation, estimation of significant single-neuron single-trial signals, mapping event-related neuronal respons...


35: Modern machine learning outperforms GLMs at predicting spikes

Ari S. Benjamin, Hugo L. Fernandes et al.

8,140 downloads (posted 24 Feb 2017)

Neuroscience has long focused on finding encoding models that effectively ask "what predicts neural spiking?" and generalized linear models (GLMs) are a typical approach. It is often unknown how much of explainable neural activity is captured, or missed, when fitting a GLM. Here we compared the predictive performance of GLMs to three leading machine learning methods: feedforward neural networks, gradient boosted trees (using XGBoost), and stacked ensembles that combine the predictions of several methods. We predicted sp...


36: Empirical assessment of published effect sizes and power in the recent cognitive neuroscience and psychology literature

Denes Szucs, John PA Ioannidis

8,063 downloads (posted 25 Aug 2016)

We have empirically assessed the distribution of published effect sizes and estimated power by extracting more than 100,000 statistical records from about 10,000 cognitive neuroscience and psychology papers published during the past 5 years. The reported median effect size was d=0.93 (inter-quartile range: 0.64-1.46) for nominally statistically significant results and d=0.24 (0.11-0.42) for non-significant results. Median power to detect small, medium and large effects was 0.12, 0.44 and 0.73, reflecting no improvement ...


37: Inferring single-trial neural population dynamics using sequential auto-encoders

Chethan Pandarinath, Daniel J. O’Shea et al.

8,035 downloads (posted 20 Jun 2017)

Neuroscience is experiencing a data revolution in which simultaneous recording of many hundreds or thousands of neurons is revealing structure in population activity that is not apparent from single-neuron responses. This structure is typically extracted from trial-averaged data. Single-trial analyses are challenging due to incomplete sampling of the neural population, trial-to-trial variability, and fluctuations in action potential timing. Here we introduce Latent Factor Analysis via Dynamical Systems (LFADS), a deep l...


38: A Critique of Pure Learning: What Artificial Neural Networks can Learn from Animal Brains

Anthony M. Zador

7,972 downloads (posted 20 Mar 2019)

Over the last decade, artificial neural networks (ANNs), have undergone a revolution, catalyzed in large part by better tools for supervised learning. However, training such networks requires enormous data sets of labeled examples, whereas young animals (including humans) typically learn with few or no labeled examples. This stark contrast with biological learning has led many in the ANN community posit that instead of supervised paradigms, animals must rely instead primarily on unsupervised learning, leading the search...


39: A Complete Electron Microscopy Volume Of The Brain Of Adult Drosophila melanogaster

Zhihao Zheng, J. Scott Lauritzen et al.

7,826 downloads (posted 22 May 2017)

Drosophila melanogaster has a rich repertoire of innate and learned behaviors. Its 100,000-neuron brain is a large but tractable target for comprehensive neural circuit mapping. Only electron microscopy (EM) enables complete, unbiased mapping of synaptic connectivity; however, the fly brain is too large for conventional EM. We developed a custom high-throughput EM platform and imaged the entire brain of an adult female fly. We validated the dataset by tracing brain-spanning circuitry involving the mushroom body (MB), in...


40: Enhancer viruses and a transgenic platform for combinatorial cell subclass-specific labeling

Lucas Graybuck, L. Daigle Tanya et al.

7,786 downloads (posted 20 Jan 2019)

The rapid pace of cell type identification by new single-cell analysis methods has not been met with efficient experimental access to the newly discovered types. To enable flexible and efficient access to specific neural populations in the mouse cortex, we collected chromatin accessibility data from individual cells and clustered the single-cell data to identify enhancers specific for cell classes and subclasses. When cloned into adeno-associated viruses (AAVs) and delivered to the brain by retro-orbital injections, the...