Materials Map

Discover the materials research landscape. Find experts, partners, networks.

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The Materials Map is an open tool for improving networking and interdisciplinary exchange within materials research. It enables cross-database search for cooperation and network partners and discovering of the research landscape.

The dashboard provides detailed information about the selected scientist, e.g. publications. The dashboard can be filtered and shows the relationship to co-authors in different diagrams. In addition, a link is provided to find contact information.

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The Materials Map is still under development. In its current state, it is only based on one single data source and, thus, incomplete and contains duplicates. We are working on incorporating new open data sources like ORCID to improve the quality and the timeliness of our data. We will update Materials Map as soon as possible and kindly ask for your patience.

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Aarhus University

in Cooperation with on an Cooperation-Score of 37%

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Publications (2/2 displayed)

  • 2021Droplet‐Based Techniques for Printing of Functional Inks for Flexible Physical Sensors151citations
  • 2021Neural correlates of beat perception measured using ear-EEGcitations

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Agarwala, Shweta
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Abdolmaleki, Hamed
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Møller, Cecilie
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Vuust, Peter
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Bliddal, Heidi
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Christensen, Christian Bech
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2021

Co-Authors (by relevance)

  • Agarwala, Shweta
  • Abdolmaleki, Hamed
  • Møller, Cecilie
  • Vuust, Peter
  • Bliddal, Heidi
  • Christensen, Christian Bech
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document

Neural correlates of beat perception measured using ear-EEG

  • Kidmose, Preben
  • Møller, Cecilie
  • Vuust, Peter
  • Bliddal, Heidi
  • Christensen, Christian Bech
Abstract

Ear-EEG is a promising novel technology that records electroencephalography (EEG), from electrodes inside the ear. This allows for a discrete and mobile recording of EEG and makes it possible to record EEG in natural environments (1). Nozaradan et al. (2011)(2) used scalp EEG to study neural responses to an isochronous sequence of sounds under three conditions: a control condition and twoimagery conditions where participants were instructed to imagine accents on every second (march) or third (waltz) beat. A significant peak was found at the frequency of the imagined beat only in the matching imagery conditions. Since no physical accents were present in the stimulus, the peaks at meter-related frequencies indicate higher order processing of the sound sequence. The aim of the present combined scalp- and ear-EEG study (n=20) was to determine whether neural correlates of beat perception can be measured using ear-EEG. To investigate this, we used an adapted version of the Nozaradan paradigm, and an additional polyrhythm paradigm. We included both in order to compare the neural correlates of instructed, induced, and spontaneous beat perception. In the polyrhythm paradigm we used an ambiguous 2:3 polyrhythm preceded by no priming or by the same rhythm emphasizing the 2-beat or the 3-beat. Comparing different kinds of beat perception is particularly important here because there could be different underlying neuronal sources depending on the nature of the beat perception. Thus, the scalp EEG might measure some sources that the ear-EEG cannot. At the time of writing data collection was still ongoing. We conducted a pilot study which included two musicians using electrodes around the ear instead of the ear-EEG used in the ongoing data collection. Pilot data using only the electrodes around the ear, obtained with the Nozaradan paradigm, showed a significantly greater amplitude at the march-related frequency in the march imagery condition compared to the control condition for one participant (p &lt;.005). The polyrhythm paradigm showed a significantly greater amplitude at the 3-beat frequency in the 3-beat condition, than the 3-beat frequency in the 2-beat condition in one participant (p&lt; .04). These preliminary results are promising for the possibility of measuring the neural correlates of beat perception with ear-EEG.<br/><br/><br/>References <br/>1. Kappel SL, Rank ML, Toft HO, Andersen M, Kidmose P. Dry-Contact Electrode Ear-EEG. IEEE Trans Biomed Eng. 2019;66(1):150–8. <br/>2. Nozaradan S, Peretz I, Missal M, Mouraux A. Tagging the neuronal entrainment to beat and meter. J Neurosci Off J Soc Neurosci. 13. juli 2011;31(28):10234–40. <br/>

Topics
  • impedance spectroscopy