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Beyond Statistical Significance: Implications of Network Structure on Neuronal Activity
University of Freiburg, Freiburg, Germany .
University of Freiburg, Freiburg, Germany .
KTH, School of Computer Science and Communication (CSC), Computational Biology, CB. University of Freiburg, Freiburg, Germany .ORCID iD: 0000-0002-8044-9195
2012 (English)In: PloS Computational Biology, ISSN 1553-734X, E-ISSN 1553-7358, Vol. 8, no 1, e1002311- p.Article in journal (Refereed) Published
Abstract [en]

It is a common and good practice in experimental sciences to assess the statistical significance of measured outcomes. For this, the probability of obtaining the actual results is estimated under the assumption of an appropriately chosen null-hypothesis. If this probability is smaller than some threshold, the results are deemed statistically significant and the researchers are content in having revealed, within their own experimental domain, a "surprising" anomaly, possibly indicative of a hitherto hidden fragment of the underlying "ground-truth". What is often neglected, though, is the actual importance of these experimental outcomes for understanding the system under investigation. We illustrate this point by giving practical and intuitive examples from the field of systems neuroscience. Specifically, we use the notion of embeddedness to quantify the impact of a neuron's activity on its downstream neurons in the network. We show that the network response strongly depends on the embeddedness of stimulated neurons and that embeddedness is a key determinant of the importance of neuronal activity on local and downstream processing. We extrapolate these results to other fields in which networks are used as a theoretical framework.

Place, publisher, year, edition, pages
2012. Vol. 8, no 1, e1002311- p.
Keyword [en]
article, cell activity, cell structure, conceptual framework, cytology, nerve cell membrane potential, nerve cell network, nerve cell stimulation, null hypothesis, probability, simulation, statistical analysis, statistical parameters, statistical significance, motor activity, nerve cell, physiology, theoretical model
National Category
Neurosciences
Identifiers
URN: urn:nbn:se:kth:diva-154849DOI: 10.1371/journal.pcbi.1002311.g003ISI: 000300218100006PubMedID: 22291581Scopus ID: 2-s2.0-84857473385OAI: oai:DiVA.org:kth-154849DiVA: diva2:758929
Note

QC 20150623

Available from: 2014-10-28 Created: 2014-10-28 Last updated: 2017-12-05Bibliographically approved

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Kumar, Arvind

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