Win–win data sharing in neuroscience

Ascoli, Giorgio A.; Maraver, Patricia; Nanda, Sumit; Polavaram, Sridevi; Armañanzas, Rubén

doi:10.1038/nmeth.4152

Cited by 75 publications

(59 citation statements)

References 23 publications

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“…To provide insights into this phenomenon, we proposed a modelling approach that considers real neurons under naturalistic conditions, receiving independent synaptic input at thousands of compartments. These detailed neurons are spatially-extended excitable trees from NeuroMorpho, a database containing over 100,000 digitally reconstructed neurons [2][3][4][35][36][37][38][39]. Here we focus our results on a set 26 neurons.…”

Section: Discussionmentioning

confidence: 99%

Spatially resolved dendritic integration: Towards a functional classification of neurons

Kirch

Gollo

2019

Preprint

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The vast tree-like dendritic structure of neurons allow them to receive and integrate input from many neurons. A wide variety of neuronal morphologies exist, however, their role in dendritic integration, and how it shapes the response of the neuron, is not yet fully understood. Here, we study the evolution and interactions of dendritic spikes in excitable neurons with complex real branch structures. We focus on dozens of digitally reconstructed illustrative neurons from the online repository NeuroMorpho.org, which contains over 100,000 neurons. Yet, our methods can be promptly extended to any other neuron. This approach allows us to estimate and map the heterogeneity of activity patterns observed across extensive dendritic trees with thousands of compartments. We propose a classification of neurons based on the location of the soma (centrality) and the dendritic topology (number of branches connected to the soma). These are key topological factors in determining the neuron's energy consumption, dynamics, and the dynamic range, which quantifies the range in synaptic input rate that can be reliably encoded by the neuron's firing rate. Moreover, we find that bifurcations, the structural building blocks of complex dendrites, play a major role in increasing the dynamic range of neurons. Our results provide a better understanding of the effects of neuronal morphology in the diversity of neuronal dynamics and function.

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Section: Discussionmentioning

confidence: 99%

Spatially resolved dendritic integration: Towards a functional classification of neurons

Kirch

Gollo

2019

Preprint

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“…First, we strongly believe that current paradigms for publication are obsolete, straining under the weight of gigantic datasets and going short of breath to catch up with the speed at which they're acquired. We not alone in expressing concern about what to do with and how to interpret the current deluge of neural, genetic and behavioral data, as well as in expressing the benefits that a culture of open science and data sharing could bring to neuroscience [57][58][59][60][61][62][63][64][65][66] .…”

Section: Curb Your Enthusiasmmentioning

confidence: 99%

Recording from the same neuron with high-density CMOS probes and patch-clamp: a ground-truth dataset and an experiment in collaboration

Marques-Smith

Neto

Lopes³

et al. 2018

Preprint

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We built a rig to perform patch-clamp and extracellular recordings from the same neuron in vivo. In this setup, the axes of two micromanipulators are precisely aligned and their relative position tracked in real-time, allowing us to accurately target patch-clamp recordings to neurons near an extracellular probe. We used this setup to generate a publicly-available dataset where a cortical neuron's spiking activity is recorded in patch-clamp next to a dense CMOS Neuropixels probe. "Ground-truth" datasets of this kind are rare but valuable to the neuroscience community, as they power the development and improvement of spike-sorting and analysis algorithms, tethering them to empirical observations. In this article, we describe our approach and report exploratory and descriptive analysis on the resulting dataset. We study the detectability of patch-clamp spikes on the extracellular probe, within-unit reliability of spike features and spatiotemporal dynamics of the action potential waveform. We open discussion and collaboration on this dataset through an online repository, with a view to producing follow-up publications. PrologueOur efforts to record from the same neuron in vivo using patch-clamp and dense extracellular probes have resulted in three outputs: a publicly-available dataset (http://bit.ly/paired_recs), a manuscript, and a code repository (http://bit.ly/paired_git). Together, these three components form the publication arising from the experiments we have performed. The role of the dataset is to be downloaded and re-used. The role of the manuscript is to describe the experimental methods through which we acquired the dataset, explain it and showcase which types of questions it can be used to address. The repository has two roles: first, promoting reproducibility and error correction.By making our analysis and figure-generation code freely-available, we wish to make our analysis procedures clear and enable the reader to reproduce our results from the raw data, alerting us to any potential mistakes. Second, the repository will form a living, dynamic and interactive component of the publication: a forum for open collaboration on this dataset. Any interested scientists can contribute to it, joining us in detailed exploration of these recordings with a view to producing follow-up publications in which they will be credited for their input.Why did we opt to publish this way? The first reason is that the very nature of the project we here describe -recording the same neuron with patch-clamp and extracellular probes -invites an open science and open source approach. This is because the primary use of this type of "ground truth" validation data is to aid the development of new sorting and analysis algorithms, as well as to benchmark and improve existing ones. The second reason is that despite being conceptually very simple, this project generated a large and complex dataset that can be tackled in many ways and used to address different types of question. Some of these questions are beyond the reach of our analytical...

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“…Some of these data have been recently made available to the public and could be used to address questions related to diversity in a large sample. A nonmutually exclusive approach, which is already emerging, albeit slowly, is for researchers to contribute to and capitalize upon publicly available data‐sharing platforms . Both approaches have the added benefits of helping to reduce the silos that exist between cognitive neuroscience laboratories, encourage transparency, allow for assessments of reproducibility, and promote “sharing of the wealth.” For cognitive neuroscientists to make use of these approaches for investigations of diversity, however, the demographic variables discussed here must first be represented in data.…”

Section: Future Directions Challenges and Opportunitiesmentioning

confidence: 99%

The importance of diversity in cognitive neuroscience

Dotson

Duarte

2019

Annals of the New York Academy of Sciences

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The vast majority of what is known about the neural underpinnings of human cognition comes from studies limited to racially, ethnically, and socioeconomically homogeneous samples. Furthermore, although most studies include both males and females in their samples, sex differences in patterns of brain activity and performance are rarely evaluated. We discuss recent research suggesting that one's socioeconomic status, race/ethnicity, and sex contribute to individual differences in neural structure, function, and related cognitive performance across a variety of cognitive domains. These studies make it clear that findings from decades of cognitive neuroscience research are likely not generalizable to a population that is much more diverse than the samples tested. We argue that these demographics cannot be ignored if we want to understand the neural substrates of human cognition for the diverse, general population. Cognitive neuroscience has been, and continues to be, used to inform education policy and clinical practice. We argue that greater diversity in cognitive neuroscience research is needed to improve reproducibility and to serve the treatment needs of a diverse population. We discuss the challenges to achieving this goal, including consideration of confounding and correlated variables, recruitment, necessary costs, and best practices for dealing with them.

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Win–win data sharing in neuroscience

Cited by 75 publications

References 23 publications

Spatially resolved dendritic integration: Towards a functional classification of neurons

Spatially resolved dendritic integration: Towards a functional classification of neurons

Recording from the same neuron with high-density CMOS probes and patch-clamp: a ground-truth dataset and an experiment in collaboration

The importance of diversity in cognitive neuroscience

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