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What are neuroinformatics and computational neuroscience?

Neuroinformatics and computational neuroscience are terms that are sometimes used interchangeably and sometimes taken to be at least partly distinct. For our purposes, we consider the terms together to encompass all computational approaches to addressing questions in neuroscience. Like the overarching field of neuroscience, it encompasses all levels of the nervous system, from molecules to behaviour, and is aimed at helping to understand the brain and ultimately improve human health.

One branch, perhaps most traditionally referred to as “computational neuroscience” and which also encompasses “theoretical neuroscience”, involves the development and application of mathematical models for understanding brain development, organization and function. Such models can incorporate various levels of complexity and biological realism and are used to formulate theories relating to computation and information processing at the cellular, neural network and systems levels. Thus, these models are constructed in order to gain better understanding as to how a particular function (e.g. memory) is implemented in a biological system (e.g. the rodent hippocampus). Importantly, these modeling efforts must be distinguished from the fields of neural computing or artificial intelligence. This is because biological realism is a premium for the computational neuroscientist. Thus experimentation is used to verify models, and to influence their further development.

Another major branch, most often described as “neuroinformatics”, deals with the methods used for acquisition, analysis, and representation of data collected from neuroscience studies. This encompasses the development and application of algorithms, statistics, databases, ontologies and data standards. Sub-branches address different modalities such as neuroimaging, behavioural studies, clinical information, electrophysiology, anatomy, genomics and proteomics, and more. Importantly, many computational efforts are targeted at integration of data across studies and modalities. The rapidly increasing complexity and volume of data collected by neuroscientists has spurred the growth of research in this area.

What brings neuroinformatics and computational neuroscience together is that more and more analysis techniques incorporate and are based on formal computational models. Conversely, without neuroinformatics we cannot extract data relevant to evaluating and constraining computational models. Bringing these fields together is natural and necessary for modern neuroscience research.

Additional information on what is encompassed by neuroinformatics and computational neuroscience can be found at the following web sites:

How do neuroinformatics and computational neuroscience relate to the rest of biomedical neuroscience in Canada?

As stated by Professor David van Essen, former President of the Society for Neuroscience, “Just as bioinformatics has profoundly impacted molecular biology and related fields, neuroinformatics has the potential for a transformative impact on neuroscience research.” Maximum benefits from neuroscience research cannot be realized without the involvement of neuroinformatics and computational neuroscience.

As data sets become larger, more complex, and more comprehensive, there is an increasing need for capacity and expertise in neuroinformatics and computational neuroscience. Of particular importance are efforts in the integration of data across studies and modalities, and in the development of models that can help transform the data into explanations. It is ever more important that neuroscientists be provided with appropriate training in computation, access to tools, and infrastructure.

A few more specific areas where computational neuroscience and neuroinformatics are playing a key role:

  • Management and analysis of functional and structural neuroimaging data.
  • Integration of neuroimaging and genetics data.
  • Management, analysis and mining of genetics, genomics and epigenetics data, in combination with clinical and phenotypic information.
  • Providing neuroscientists with easy access to high-performance computing infrastructure.
  • Providing neuroscientists with key resources aggregating neuroscience data.
  • Development of standards that enable collaborations and reproducibility of experiments.
  • Mechanistic explanations of fundamental processes underlying brain function.
  • A compact means to synthesize huge amounts of complicated-looking data through few compact models.
  • Enabling predictions for meaningful and important experiments, especially when involving animals or patients, for whom the number of invasive studies should be minimized.
  • A means to identify hidden assumptions and formalize “word models”.
  • Modeling neurological diseases, accelerating the development of treatments, rehabilitation strategies and improving of quality of life.
  • Enabling brain-computer interfaces.

History

Member of the steering committee have had longstanding plans to get together and organize a formal Neurocomputing and Computational Neuroscience community. It was at a recent Canadian Neuroinformatics workshop that our enthousiasm finally reached the critical threshold to get us going. A report of the workshop can be downloaded here.

The first Canadian Neuroinformatics Workshop was held in Vancouver on May 24th 2012. It was co-organized by the NeuroDevNet Neuroinformatics Core and the International Neuroinformatics Coordinating Facility (INCF) as a satellite symposium of the Canadian Neuroscience Meeting. This workshop featured ten Canadian speakers working in one of the many areas encompassed by the field, including neuroimaging, computational modeling, clinical neuroinformatics, and neurogenomics. INCF activities were also presented by the INCF executive director as well as two US researchers, with the idea to discuss about benefits and strategies for Canada to join the INCF organization.

The workshop was open and free to attend to the whole neuroscience research community. Many registered and had to be placed on a waiting list, demonstrating the huge interest the Neuroinformatics field has for a broader community. It also helped foster the emergence of a Canadian neuroinformatics steering committee which is currently working to improve the visibility of the field and hopefully help develop new funding and training opportunities.

The development of the neuroinfocomp.ca website is the first initiative arising from this committee and will be the central point where future initiatives will be announced and released.

Get involved by joining our growing community!