Lecture

In Silico Neuroscience: Data Reproducibility and Reusability

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In course

BIOENG-450: In silico neuroscience

"In silico Neuroscience" introduces students to a synthesis of modern neuroscience and state-of-the-art data management, modelling and computing technologies. ...

Description

This lecture covers the importance of data reproducibility and reusability in in silico neuroscience, focusing on neuroinformatics tools and methods. It discusses challenges in finding, storing, analyzing, and publishing neuroscience data, emphasizing the need for standardized metadata and controlled vocabularies. The lecture also explores the concepts of provenance, metadata quality, and the Minimal Information for Neuroscience Datasets (MINDS) standard. It highlights the significance of ontology, standard vocabulary, and the FAIR Guiding Principles for data findability, accessibility, interoperability, and reusability. The Blue Brain Project's efforts in simulation neuroscience and the integration of software and hardware ecosystems are also discussed.

Instructors (2)

Felix Schürmann

Felix Schürmann is co-director of the Blue Brain Project and involved in several research challenges of the European Human Brain Project. He studied physics at the University of Heidelberg, Germany, supported by the German National Academic Foundation. Later, as a Fulbright Scholar, he obtained his Master's degree (M.S.) in Physics from the State University of New York, Buffalo, USA, under the supervision of Richard Gonsalves. During these studies, he became curious about the role of different computing substrates and dedicated his master thesis to the simulation of quantum computing. He studied for his Ph.D. at the University of Heidelberg, Germany, under the supervision of Karlheinz Meier. For his thesis he co-designed an efficient implementation of a neural network in hardware.

Armando Romani

Official source

Related concepts (32)

Data

In common usage and statistics, data (USˈdætə; UKˈdeɪtə) is a collection of discrete or continuous values that convey information, describing the quantity, quality, fact, statistics, other basic units of meaning, or simply sequences of symbols that may be further interpreted formally. A datum is an individual value in a collection of data. Data is usually organized into structures such as tables that provide additional context and meaning, and which may themselves be used as data in larger structures.

FAIR data

FAIR data are data which meet principles of findability, accessibility, interoperability, and reusability (FAIR). The acronym and principles were defined in a March 2016 paper in the journal Scientific Data by a consortium of scientists and organizations. The FAIR principles emphasize machine-actionability (i.e., the capacity of computational systems to find, access, interoperate, and reuse data with none or minimal human intervention) because humans increasingly rely on computational support to deal with data as a result of the increase in volume, complexity, and creation speed of data.

Data quality

Data quality refers to the state of qualitative or quantitative pieces of information. There are many definitions of data quality, but data is generally considered high quality if it is "fit for [its] intended uses in operations, decision making and planning". Moreover, data is deemed of high quality if it correctly represents the real-world construct to which it refers. Furthermore, apart from these definitions, as the number of data sources increases, the question of internal data consistency becomes significant, regardless of fitness for use for any particular external purpose.

Romani diaspora

The Romani people have several distinct populations, the largest being the Roma and the Calé, who reached Anatolia and the Balkans in the early 12th century, from a migration out of the Indian subcontinent beginning about 1st century – 2nd century AD. They settled in the areas of present-day Turkey, Greece, Serbia, Romania, Croatia, Moldova, Bulgaria, North Macedonia, Hungary, Albania, Kosovo, Bosnia and Herzegovina, Czech Republic, Slovenia and Slovakia, by order of volume, and Spain.

Neuroinformatics

Neuroinformatics is the field that combines informatics and neuroscience. Neuroinformatics is related with neuroscience data and information processing by artificial neural networks. There are three main directions where neuroinformatics has to be applied: the development of computational models of the nervous system and neural processes.

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