An information science infrastructure for neuroscience

@article{Ascoli2003AnIS,
  title={An information science infrastructure for neuroscience},
  author={Giorgio A. Ascoli and Erik De Schutter and David N. Kennedy},
  journal={Neuroinformatics},
  year={2003},
  volume={1},
  pages={1-2}
}
in all areas of neuroscience in the past few decades. As research in neuroscience continues to advance, the capacity of the individual investigator to retain all relevant information is severely taxed. This data, and the subsequent analytic results and conclusions that are generated , is derived from a myriad of diverse experiments that span scale, species, development , and pathology. This glut of information simultaneously provides a unique opportunity and a daunting challenge. The… 
Neuron and Network Modeling
TLDR
This chapter describes the state of the art in neuron and network modeling, with particular emphasis on the methods to acquire, analyze, and synthesize neuroanatomical data.
Domain-Specific Data Sharing in Neuroscience: What Do We Have to Learn from Each Other?
TLDR
This article discusses how neuroscience domains might follow the lead of molecular biology on what has been successful and what has failed in active data sharing, and considers not only the technical challenges but also the sociological concerns in making it possible.
Mobilizing the base of neuroscience data: the case of neuronal morphologies
  • G. Ascoli
  • Biology
    Nature Reviews Neuroscience
  • 2006
TLDR
It is argued that the tremendous research potential of existing (and largely unused) digital reconstructions should diffuse any reticence to sharing this type of data.
Using semantic web techniques for validation of cognitive models against neuroscientific data
TLDR
This work has shown that many structural and functional claims about a model could be automatically validated against neuroscientific data if both the model and the data were represented in form suitable for an inference engine.
On Neuroinformatics: Mathematical Models of Neuroscience and Neurocomputing
TLDR
A mathematical treatment of the neurological models and neural signal theories is formally described covering neural signal generation, pulse frequency modulation, and the multiplexer/demultiplexer for neural signal transmissions.
Atlas-based neuroinformatics via MRI: harnessing information from past clinical cases and quantitative image analysis for patient care.
TLDR
The potential of atlas-based clinical neuroinformatics, which consists of annotated databases of anatomical measurements grouped according to their morphometric phenotypes and coupled with the clinical informatics upon which their diagnostic groupings are based, is discussed.
MRI‐based morphometric analysis of typical and atypical brain development
The neuroinformatics landscape in which human brain morphometry occurs has advanced dramatically over the past few years. Rapid advancement in image acquisition methods, image analysis tools and
A Neural Circuit Theory for Neuroinformatics and Brain-Machine Interactions
  • Yingxu Wang, Jin Jiu, Liu Lin
  • Psychology, Computer Science
    2019 IEEE International Conference on Systems, Man and Cybernetics (SMC)
  • 2019
TLDR
A novel neural circuit theory for analytic neurology and formal neuroinformatics is presented, which explains the formation of temporal thinking threads, permanent memory, and knowledge representations in the brain and their interfaces to machines and neurocomputing systems.
The Spike Frequency Modulation (SFM) Theory for Neuroinformatics and Cognitive Cybernetics
  • Yingxu Wang, N. Howard
  • Psychology, Biology
    2019 IEEE International Conference on Systems, Man and Cybernetics (SMC)
  • 2019
TLDR
The SFM theory reveals the neurological and cognitive foundations of both natural and artificial neural networks for brain-inspired systems and engineering applications.
...
...