Engineering the Next Revolution in Neuroscience

Silva, Alcino J.; Landreth, Anthony

doi:10.1093/acprof:oso/9780199731756.001.0001

Cited by 27 publications

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Section: Research Maps For Molecular and Cellular Cognitionmentioning

confidence: 99%

“…Here, we propose the development of semiautomated graphical and interactive tools to help neuroscientists and other biologists, including those working in molecular and cellular cognition, to track, map, and weight causal evidence in research papers. There is a great need for a concerted effort by biologists, computer scientists, and funding institutions to develop maps of causal information that would aid in integration of research findings and in experiment planning.Information in biology, including neuroscience, is growing at an unprecedented pace that demands new tools and new approaches (Lok 2010;Silva et al 2014). Because of the ever-growing number, complexity, and interconnectedness of research publications and biological concepts, it is simply no longer possible for individual biologists to be aware of even a fraction of the published findings potentially pertinent to their work.…”

mentioning

confidence: 99%

“…These private maps of unpublished information are a real help in deciding how to best complement existing experiments before submitting a manuscript for publication. Although there is a freely available web-driven interface for assembling and interacting with research maps (www.researchmaps.org), users can draw their own maps with nothing more than pen and paper (Landreth and Silva 2013;Silva et al 2014).Beyond representations of published experiments, research maps could also be linked to the growing number of biological resources that curate large bodies of information about genes, proteins, cells, biological systems, clinical resources, etc. These resources would be not only accessible from research maps, they would also be appropriately integrated with the nodes and edges of these maps.…”

mentioning

confidence: 99%

“…Information in biology, including neuroscience, is growing at an unprecedented pace that demands new tools and new approaches (Lok 2010;Silva et al 2014). Because of the ever-growing number, complexity, and interconnectedness of research publications and biological concepts, it is simply no longer possible for individual biologists to be aware of even a fraction of the published findings potentially pertinent to their work.…”

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confidence: 99%

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The need for novel informatics tools for integrating and planning research in molecular and cellular cognition

Silva

Müller

2015

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The sheer volume and complexity of publications in the biological sciences are straining traditional approaches to research planning. Nowhere is this problem more serious than in molecular and cellular cognition, since in this neuroscience field, researchers routinely use approaches and information from a variety of areas in neuroscience and other biology fields. Additionally, the multilevel integration process characteristic of this field involves the establishment of experimental connections between molecular, electrophysiological, behavioral, and even cognitive data. This multidisciplinary integration process requires strategies and approaches that originate in several different fields, which greatly increases the complexity and demands of this process. Although causal assertions, where phenomenon A is thought to contribute or relate to B, are at the center of this integration process and key to research in biology, there are currently no tools to help scientists keep track of the increasingly more complex network of causal connections they use when making research decisions. Here, we propose the development of semiautomated graphical and interactive tools to help neuroscientists and other biologists, including those working in molecular and cellular cognition, to track, map, and weight causal evidence in research papers. There is a great need for a concerted effort by biologists, computer scientists, and funding institutions to develop maps of causal information that would aid in integration of research findings and in experiment planning.Information in biology, including neuroscience, is growing at an unprecedented pace that demands new tools and new approaches (Lok 2010;Silva et al. 2014). Because of the ever-growing number, complexity, and interconnectedness of research publications and biological concepts, it is simply no longer possible for individual biologists to be aware of even a fraction of the published findings potentially pertinent to their work. The library of medicine, for example, now includes more than 25 million research papers reporting the results of at least 100 million experiments. Even a young field like Molecular and Cellular Cognition includes tens of thousands of research papers reporting millions of experiments. When the implications of what has already been published remain buried in the never-ending avalanche of published information, how can scientists reasonably optimize future research plans? Although there is a great deal of work on-going to tackle different components of this problem, from annotation of the literature, to curation of databases and automated reasoning, much remains to be done. Here, we address the need for graphical and interactive tools that track and map causal evidence in research papers (i.e., research maps). Although causal assertions are the very fabric of biology, there are currently no tools to help biologists keep track of the increasingly more complex network of causal connections derived from published findings. A causal connection is defined by ev...

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Section: Research Maps For Molecular and Cellular Cognitionmentioning

confidence: 99%

mentioning

confidence: 99%

mentioning

confidence: 99%

mentioning

confidence: 99%

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The need for novel informatics tools for integrating and planning research in molecular and cellular cognition

Silva

Müller

2015

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“…This further precludes the integration of knowledge in neuroscience given that neurobiology is an integral part of neuroscience. This result is unsettling for both neuroscience and philosophy of neuroscience, especially given that Sullivan's analysis was the only systematic account of experimentation in neuroscience until Silva, Landreth, and Bickle (2014) recently came out of press. It explicitly challenges leading philosophical accounts of neuroscience such as Bickle (2006), Craver (2007), and Bechtel (2008) among others.…”

Section: Introductionmentioning

confidence: 99%

Validating Animal Models

Atanasova

2015

THEORIA

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This paper responds to a recent challenge for the validity of extrapolation of neurobiological knowledge from laboratory animals to humans. According to this challenge, experimental neurobiology, and thus neuroscience, is in a state of crisis because the knowledge produced in different laboratories hardly generalizes from one laboratory to another. Presumably, this is so because neurobiological laboratories use simplified animal models of human conditions that differ across laboratories. By contrast, I argue that maintaining a multiplicity of experimental protocols and simple models is well justified. It fosters rather than precludes the validity of extrapolation of neurobiological knowledge. The discipline is thriving.Keywords: Animal Models, Calibration, Validity, Reliability, Experimental Neurobiology.RESUMEN: Este artículo responde a un reto reciente: la validez de extrapolar el conocimiento neurobiológico del laboratorio animal a los humanos. Según esta objeción la neurobiología experimental, y por ende la neurociencia, está en crisis porque el conocimiento obtenido en los laboratorios de neurobiología utiliza modelos animales simplificados de las condiciones humanas que difieren de unos laboratorios a otros. Por el contrario, sostengo que mantener una diversidad de protocolos experimentales y de modelos simples está sobradamente justificado. Favorece, en vez de impedir, la validez de la extrapolación de conocimiento neurobiológico. La neurobiología es una disciplina floreciente.

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Introduction

Mondal

2019

Language, Biology and Cognition

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Engineering the Next Revolution in Neuroscience

Cited by 27 publications

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The need for novel informatics tools for integrating and planning research in molecular and cellular cognition

The need for novel informatics tools for integrating and planning research in molecular and cellular cognition

Validating Animal Models

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