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Currently indexing 64,995 bioRxiv papers from 288,040 authors.

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Results 21 through 40 out of 11386

in category neuroscience

 

21: Molecular architecture of the mouse nervous system

Amit Zeisel, Hannah Hochgerner et al.

9,339 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 genes encoding cell identity, synaptic connectivity, neurotransmission and membrane conductance. We discovered several distinct, regionally restricted, astrocytes types, which obeyed developmental boundaries and correlated with the spatial distribution of key glutamate and glycine neurotransmitters. In contrast, oligodendrocytes showed a loss of regional identity, followed by a secondary diversi cation. The resource presented here lays a solid foundation for understanding the molecular architecture of the mammalian nervous system, and enables genetic manipulation of specific cell types.

https://rxivist.org/papers/13168
https://doi.org/10.1101/294918

22: 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.

8,933 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...

https://rxivist.org/papers/13012
https://doi.org/10.1101/299081

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

Rosemary C Challis, Sripriya Ravindra Kumar et al.

8,617 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...

https://rxivist.org/papers/13884
https://doi.org/10.1101/246405

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

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

8,373 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...

https://rxivist.org/papers/46102
https://doi.org/10.1101/578542

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

Marius Pachitariu, Nicholas Steinmetz et al.

8,270 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...

https://rxivist.org/papers/16344
https://doi.org/10.1101/061481

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

Cleber A. Trujillo, Richard D Gao et al.

8,100 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 ...

https://rxivist.org/papers/12226
https://doi.org/10.1101/358622

27: A neural algorithm for a fundamental computing problem

Sanjoy Dasgupta, Charles F Stevens et al.

8,013 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...

https://rxivist.org/papers/14952
https://doi.org/10.1101/180471

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

Denes Szucs, John PA Ioannidis

7,931 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 ...

https://rxivist.org/papers/16258
https://doi.org/10.1101/071530

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

Carsen Stringer, Marius Pachitariu et al.

7,590 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...

https://rxivist.org/papers/11611
https://doi.org/10.1101/374090

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

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

7,542 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...

https://rxivist.org/papers/15330
https://doi.org/10.1101/152884

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

Zhihao Zheng, J. Scott Lauritzen et al.

7,453 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...

https://rxivist.org/papers/15377
https://doi.org/10.1101/140905

32: Cortical Column and Whole Brain Imaging of Neural Circuits with Molecular Contrast and Nanoscale Resolution

Ruixuan Gao, Shoh M Asano et al.

7,428 downloads (posted 23 Jul 2018)

Optical and electron microscopy have made tremendous inroads in understanding the complexity of the brain, but the former offers insufficient resolution to reveal subcellular details and the latter lacks the throughput and molecular contrast to visualize specific molecular constituents over mm-scale or larger dimensions. We combined expansion microscopy and lattice light sheet microscopy to image the nanoscale spatial relationships between proteins across the thickness of the mouse cortex or the entire Drosophila brain,...

https://rxivist.org/papers/11930
https://doi.org/10.1101/374140

33: Modern machine learning outperforms GLMs at predicting spikes

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

7,353 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...

https://rxivist.org/papers/14689
https://doi.org/10.1101/111450

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

Anthony M Zador

7,260 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...

https://rxivist.org/papers/46472
https://doi.org/10.1101/582643

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

Peter H Li, Larry F. Lindsey et al.

7,141 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...

https://rxivist.org/papers/48317
https://doi.org/10.1101/605634

36: Wide field-of-view, twin-region two-photon imaging across extended cortical networks

Jeffrey N. Stirman, Ikuko T. Smith et al.

7,096 downloads (posted 12 Nov 2014)

We demonstrate a two-photon imaging system with corrected optics including a custom objective that provides cellular resolution across a 3.5 mm field of view (9.6 mm^2). Temporally multiplexed excitation pathways can be independently repositioned in XY and Z to simultaneously image regions within the expanded field of view. We used this new imaging system to measure activity correlations between neurons in different cortical areas in awake mice.

https://rxivist.org/papers/16610
https://doi.org/10.1101/011320

37: 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.

7,020 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...

https://rxivist.org/papers/15687
https://doi.org/10.1101/103879

38: 7 Tesla MRI of the ex vivo human brain at 100 micron resolution

Brian L Edlow, Azma Mareyam et al.

6,987 downloads (posted 31 May 2019)

We present an ultra-high resolution magnetic resonance imaging (MRI) dataset of an ex vivo human brain specimen. The brain specimen was donated by a 58-year-old woman who had no history of neurological disease and died of non-neurological causes. After fixation in 10% formalin, the specimen was imaged on a 7 Tesla MRI scanner at 100 micron isotropic resolution using a custom-built 31-channel receive array coil. Single-echo multi-flip Fast Low-Angle SHot (FLASH) data were acquired over 100 hours of scan time (25 hours pe...

https://rxivist.org/papers/52089
https://doi.org/10.1101/649822

39: Prefrontal cortical control of a brainstem social behavior circuit

Tamara B. Franklin, Bianca A. Silva et al.

6,918 downloads (posted 09 Sep 2016)

The prefrontal cortex plays a critical role in adjusting an organism's behavior to its environment. In particular, numerous studies have implicated the prefrontal cortex in the control of social behavior, but the neural circuits that mediate these effects remain unknown. Here we investigated behavioral adaptation to social defeat in mice and uncovered a critical contribution of neural projections from the medial prefrontal cortex to the dorsal periaqueductal grey, a brainstem area vital for defensive responses. Social d...

https://rxivist.org/papers/16234
https://doi.org/10.1101/073734

40: Natural image reconstruction from brain waves: a novel visual BCI system with native feedback

Grigory V. Rashkov, Anatoly S. Bobe et al.

6,655 downloads (posted 01 Oct 2019)

Here we hypothesize that observing the visual stimuli of different categories trigger distinct brain states that can be decoded from noninvasive EEG recordings. We introduce an effective closed-loop BCI system that reconstructs the observed or imagined stimuli images from the co-occurring brain wave parameters. The reconstructed images are presented to the subject as a visual feedback. The developed system is applicable to training BCI-naive subjects because of the user-friendly and intuitive way the visual patterns are...

https://rxivist.org/papers/62246
https://doi.org/10.1101/787101