Minimum Information about a Neuroscience Investigation (MINI): Electrophysiology

Gibson, F.; Overton, Paul G.; Smulders, Tom V.; Schultz, Simon R.; Eglen, Stephen J.; Ingram, C.D.; Panzeri, Stefano; Bream, Phil; Whittington, Miles A.; Sernagor, Evelyne; Cunningham, Mark; Adams, Christopher; Echtermeyer, Christoph; Simonotto, Jennifer; Kaiser, Marcus; Swan, Daniel; Fletcher, Martyn; Lord, Phillip

doi:10.1038/npre.2009.1720.2

Cited by 19 publications

(17 citation statements)

References 1 publication

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“…57 MIMs generally focus on specific types of investigations or experiments, and are especially popular in crossdisciplinary fields such as experimental biology. [47][48][49] MIMs must be discipline-specific in order to provide appropriate, applicable reporting standards. 47 As discussed above, adherence to the MIM ensures that: (i) metadata needed in interpretation of experimental data is collected; and (ii) that the experiment is described in sufficient detail that it can be repeated accurately.…”

Section: Description and Advantagesmentioning

confidence: 99%

“…Following the success of MIAME, minimum information standards were taken up by other scientific communities. [47][48][49][50][60][61][62][63][64][65][66] However, to date no MIMs have been developed that describe dielectric measurements of biological tissues. The lack of such a reporting standard is contributing to inconsistency in both the resulting data, and in the types of metadata that are presented or published alongside the data.…”

Section: Current State-of-the-artmentioning

confidence: 99%

“…Minimum information models have been used with success in other biology-related disciplines, for example, in cardiac experimental electrophysiology (MICEE), 47 proteomics (MIAPE), 48 neuroscience (MINI), 49 and genomic investigations (MIBBI). 50 The use of a similar type of reporting standard would greatly benefit the field of dielectric metrology for biological tissues.…”

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confidence: 99%

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Minimum information for dielectric measurements of biological tissues (MINDER): A framework for repeatable and reusable data

Porter

Gioia

Salahuddin

et al. 2017

Int J RF Microw Comput Aided Eng

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The dielectric properties of biological tissues characterise the interaction of human tissues with electromagnetic (EM) fields. Accurate knowledge of the dielectric properties of tissues are vital in EM‐based therapeutic and diagnostic techniques, and for assessing the safety of wireless devices. Despite the importance of these properties, the field has suffered from inconsistencies in reported data. The dielectric measurement process for tissues is known to be affected by both measurement confounders and clinical confounders; however, adequate metadata is often lacking in the literature. For this reason, this work proposes a standard, called Minimum Information for Dielectric Measurements of Biological Tissues (MINDER). In the MINDER model, the minimum types of raw data and metadata needed to interpret or replicate a dielectric study are identified and described. Alongside the minimum information model, a controlled vocabulary for metadata parameters is proposed. We also provide an example of this model applied to a dielectric measurement scenario on a biological tissue sample. The MINDER model enables reproducibility of measurements, ease of interpreting and re‐using data, and comparison of data across studies. Further, this standard framework will support dielectric databases, with data searchable through metadata parameters such as temperature, frequency range, tissue type, and tissue state.

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Section: Description and Advantagesmentioning

confidence: 99%

Section: Current State-of-the-artmentioning

confidence: 99%

mentioning

confidence: 99%

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Minimum information for dielectric measurements of biological tissues (MINDER): A framework for repeatable and reusable data

Porter

Gioia

Salahuddin

et al. 2017

Int J RF Microw Comput Aided Eng

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“…As a result of our experience with complex analysis of experiments in systems neuroscience as reported in this paper, one of our recommendations is to record as much information about the experiment as possible. This may seem in contrast to efforts specifying minimal information guidelines in the life sciences (MIBBI; Taylor et al, 2008 , MINI; Gibson et al, 2009 ). However, those initiatives target the use case where data are uploaded to a public database, and their goal is to achieve a balance of information detail such that the minimally sufficient information is provided to make the data potentially useful for the community.…”

Section: Discussionmentioning

confidence: 89%

Handling Metadata in a Neurophysiology Laboratory

Zehl

Jaillet

Adrian

et al. 2016

Front. Neuroinform.

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To date, non-reproducibility of neurophysiological research is a matter of intense discussion in the scientific community. A crucial component to enhance reproducibility is to comprehensively collect and store metadata, that is, all information about the experiment, the data, and the applied preprocessing steps on the data, such that they can be accessed and shared in a consistent and simple manner. However, the complexity of experiments, the highly specialized analysis workflows and a lack of knowledge on how to make use of supporting software tools often overburden researchers to perform such a detailed documentation. For this reason, the collected metadata are often incomplete, incomprehensible for outsiders or ambiguous. Based on our research experience in dealing with diverse datasets, we here provide conceptual and technical guidance to overcome the challenges associated with the collection, organization, and storage of metadata in a neurophysiology laboratory. Through the concrete example of managing the metadata of a complex experiment that yields multi-channel recordings from monkeys performing a behavioral motor task, we practically demonstrate the implementation of these approaches and solutions with the intention that they may be generalized to other projects. Moreover, we detail five use cases that demonstrate the resulting benefits of constructing a well-organized metadata collection when processing or analyzing the recorded data, in particular when these are shared between laboratories in a modern scientific collaboration. Finally, we suggest an adaptable workflow to accumulate, structure and store metadata from different sources using, by way of example, the odML metadata framework.

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“…The enabling nature of rich metadata descriptors, however, is not restricted to the purview of digital reconstructions, but can rather benefit all fields of neuroscience investigating neuronal properties at large, including electrophysiology (Gibson et al 2009) and neurochemistry. A useful step forward would be for scientific journals to request analogous metadata information from authors upon accepting manuscripts for publication.…”

Section: Discussionmentioning

confidence: 99%

The importance of metadata to assess information content in digital reconstructions of neuronal morphology

2015

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Digital reconstructions of axonal and dendritic arbors provide a powerful representation of neuronal morphology in formats amenable to quantitative analysis, computational modeling, and data mining. Reconstructed files, however, require adequate metadata to identify the appropriate animal species, developmental stage, brain region, and neuron type. Moreover, experimental details about tissue processing, neurite visualization and microscopic imaging are essential to assess the information content of digital morphologies. Typical morphological reconstructions only partially capture the underlying biological reality. Tracings are often limited to certain domains (e.g. dendrites and not axons), may be incomplete due to tissue sectioning, imperfect staining, and limited imaging resolution, or can disregard aspects irrelevant to their specific scientific focus (such as branch thickness or depth). Gauging these factors is critical in subsequent data reuse and comparison. NeuroMorpho.Org is a central repository of reconstructions from many laboratories and experimental conditions. Here we introduce substantial additions to the existing metadata annotation aimed to describe the completeness of the reconstructed neurons in NeuroMorpho.Org. These expanded metadata form a suitable basis for effective description of neuromorphological data.

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Minimum Information about a Neuroscience Investigation (MINI): Electrophysiology

Abstract: This module represents the formalised opinion of the authors and the CARMEN consortium, which identifies the minimum information required to report the use of electrophysiology in a neuroscience study, for submission to the CARMEN system (www.carmen.org.uk).

Cited by 19 publications

References 1 publication

Minimum information for dielectric measurements of biological tissues (MINDER): A framework for repeatable and reusable data

Minimum information for dielectric measurements of biological tissues (MINDER): A framework for repeatable and reusable data

Handling Metadata in a Neurophysiology Laboratory

The importance of metadata to assess information content in digital reconstructions of neuronal morphology

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