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Institution

Indiana University

EducationBloomington, Indiana, United States
About: Indiana University is a education organization based out in Bloomington, Indiana, United States. It is known for research contribution in the topics: Population & Poison control. The organization has 64480 authors who have published 150058 publications receiving 6392902 citations. The organization is also known as: Indiana University system & indiana.edu.


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Journal ArticleDOI

1,696 citations

Journal ArticleDOI
TL;DR: Simulating nonlinear neuronal dynamics on a network that captures the large-scale interregional connections of macaque neocortex, and applying information theoretic measures to identify functional networks, this work finds structure–function relations at multiple temporal scales.
Abstract: Neuronal dynamics unfolding within the cerebral cortex exhibit complex spatial and temporal patterns even in the absence of external input. Here we use a computational approach in an attempt to relate these features of spontaneous cortical dynamics to the underlying anatomical connectivity. Simulating nonlinear neuronal dynamics on a network that captures the large-scale interregional connections of macaque neocortex, and applying information theoretic measures to identify functional networks, we find structure-function relations at multiple temporal scales. Functional networks recovered from long windows of neural activity (minutes) largely overlap with the underlying structural network. As a result, hubs in these long-run functional networks correspond to structural hubs. In contrast, significant fluctuations in functional topology are observed across the sequence of networks recovered from consecutive shorter (seconds) time windows. The functional centrality of individual nodes varies across time as interregional couplings shift. Furthermore, the transient couplings between brain regions are coordinated in a manner that reveals the existence of two anticorrelated clusters. These clusters are linked by prefrontal and parietal regions that are hub nodes in the underlying structural network. At an even faster time scale (hundreds of milliseconds) we detect individual episodes of interregional phase-locking and find that slow variations in the statistics of these transient episodes, contingent on the underlying anatomical structure, produce the transfer entropy functional connectivity and simulated blood oxygenation level-dependent correlation patterns observed on slower time scales.

1,695 citations

Journal ArticleDOI
01 Nov 2017-Nature
TL;DR: A meta-analysis of microbial community samples collected by hundreds of researchers for the Earth Microbiome Project is presented, creating both a reference database giving global context to DNA sequence data and a framework for incorporating data from future studies, fostering increasingly complete characterization of Earth’s microbial diversity.
Abstract: Our growing awareness of the microbial world’s importance and diversity contrasts starkly with our limited understanding of its fundamental structure. Despite recent advances in DNA sequencing, a lack of standardized protocols and common analytical frameworks impedes comparisons among studies, hindering the development of global inferences about microbial life on Earth. Here we present a meta-analysis of microbial community samples collected by hundreds of researchers for the Earth Microbiome Project. Coordinated protocols and new analytical methods, particularly the use of exact sequences instead of clustered operational taxonomic units, enable bacterial and archaeal ribosomal RNA gene sequences to be followed across multiple studies and allow us to explore patterns of diversity at an unprecedented scale. The result is both a reference database giving global context to DNA sequence data and a framework for incorporating data from future studies, fostering increasingly complete characterization of Earth’s microbial diversity.

1,676 citations

Journal ArticleDOI
TL;DR: The following is the first publication of an English translation that has been authorized and reviewed by Mori and explored its implications for human-robot interaction and computer-graphics animation, whereas others have investigated its biological and social roots.
Abstract: More than 40 years ago, Masahiro Mori, a robotics professor at the Tokyo Institute of Technology, wrote an essay [1] on how he envisioned people's reactions to robots that looked and acted almost like a human. In particular, he hypothesized that a person's response to a humanlike robot would abruptly shift from empathy to revulsion as it approached, but failed to attain, a lifelike appearance. This descent into eeriness is known as the uncanny valley. The essay appeared in an obscure Japanese journal called Energy in 1970, and in subsequent years, it received almost no attention. However, more recently, the concept of the uncanny valley has rapidly attracted interest in robotics and other scientific circles as well as in popular culture. Some researchers have explored its implications for human-robot interaction and computer-graphics animation, whereas others have investigated its biological and social roots. Now interest in the uncanny valley should only intensify, as technology evolves and researchers build robots that look human. Although copies of Mori's essay have circulated among researchers, a complete version hasn't been widely available. The following is the first publication of an English translation that has been authorized and reviewed by Mori. (See “Turning Point” in this issue for an interview with Mori.).

1,669 citations

Journal ArticleDOI
TL;DR: Reflecting the internationalization of the marketplace and the increasing prominence of entrepreneurial firms in the global economy, the research paths of international business and entrepreneur-shi... as mentioned in this paper ].
Abstract: Reflecting the internationalization of the marketplace and the increasing prominence of entrepreneurial firms in the global economy, the research paths of international business and entrepreneurshi...

1,667 citations


Authors

Showing all 64884 results

NameH-indexPapersCitations
Frank B. Hu2501675253464
Stuart H. Orkin186715112182
Bruce M. Spiegelman179434158009
David R. Williams1782034138789
D. M. Strom1763167194314
Markus Antonietti1761068127235
Lei Jiang1702244135205
Brenda W.J.H. Penninx1701139119082
Nahum Sonenberg167647104053
Carl W. Cotman165809105323
Yang Yang1642704144071
Jaakko Kaprio1631532126320
Ralph A. DeFronzo160759132993
Gavin Davies1592036149835
Tyler Jacks158463115172
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
2023127
2022694
20217,272
20207,310
20196,943
20186,496