Testing two-step models of negative quantification using a novel machine learning analysis of EEG

S. Ramotowskaa Institute for Logic, Language and Computation, University of Amsterdam, Amsterdam, The NetherlandsCorrespondence[email protected] [email protected]

https://orcid.org/0000-0003-3381-4089 View further author information

K. Archambeaub Université Libre de Bruxelles, Bruxelles, BelgiumView further author information

P. Augurzkyc Department of Psychology, Universität Tübingen, Tübingen, GermanyView further author information

F. Schlotterbeckd Institute of German Language and Literatures, Universität Tübingen, Tübingen, Germany

https://orcid.org/0000-0002-2310-9151 View further author information

H.S. Berberyane Bernoulli Institute, University of Groningen, Groningen, The NetherlandsView further author information

L. Van Maanenf Department of Experimental Psychology & Helmholtz Institute, Utrecht University, Utrecht, The NetherlandsView further author information

J. Szymanikg Center for Mind/Brain Sciences and Dept. of Information Engineering and Computer Science, University of Trento, Trento TN, ItalyView further author information

show all

Testing two-step models of negative quantification using a novel machine learning analysis of EEG

Information for

Open access

Opportunities

Help and information

Your download is now in progress and you may close this window

Login or register to access this feature

Testing two-step models of negative quantification using a novel machine learning analysis of EEG

Citations (0)

Related research

To cite this article:

Download citation

Information for

Open access

Opportunities

Help and information

Keep up to date