When an adult claims he cannot sleep without his teddy bear, people tend to react surprised. Language interpretation is, thus, influenced by social context, such as who the speaker is. The present study reveals inter-individual differences in brain reactivity to social aspects of language. Whereas women showed brain reactivity when stereotype-based inferences about a speaker conflicted with the content of the message, men did not. This sex difference in social information processing can be explained by a specific cognitive trait, one's ability to empathize. Individuals who empathize to a greater degree revealed larger N400 effects (as well as a larger increase in γ-band power) to socially relevant information. These results indicate that individuals with high-empathizing skills are able to rapidly integrate information about the speaker with the content of the message, as they make use of voice-based inferences about the speaker to process language in a top-down manner. Alternatively, individuals with lower empathizing skills did not use information about social stereotypes in implicit sentence comprehension, but rather took a more bottom-up approach to the processing of these social pragmatic sentences.
MULTIFILE
Dit onderzoek is bedoeld om de huidige labelvorming van kinderen met luisterproblemen te onderzoeken en om in samenwerking met logopedisten en audiologen in Nederland te komen tot een uniforme en hanteerbare definitie en om de kennis en ervaring op het gebied van signalering, diagnostiek en behandeling te bundelen. De aanleiding voor dit promotieonderzoek zijn de vragen vanuit het werkveld (logopedisten, audiologen, psychologen AC) over AVP die tijdens presentaties op diverse congressen, in logopedische kwaliteitskringen en dyslexiekringen in de periode 2008-2012 en tijdens de studiedag “Diagnostiek van auditieve verwerkingsproblemen” van de FENAC op 21 mei 2014 (http://www.fenac.nl/algemeen/opleiding/studiedag-avp/studiedag-diagnostiek-van-auditieve-verwerkingsproblemen-avp.html) gesteld werden.
DOCUMENT
Electrohydrodynamic Atomization (EHDA), also known as Electrospray (ES), is a technology which uses strong electric fields to manipulate liquid atomization. Among many other areas, electrospray is currently used as an important tool for biomedical applications (droplet encapsulation), water technology (thermal desalination and metal recovery) and material sciences (nanofibers and nano spheres fabrication, metal recovery, selective membranes and batteries). A complete review about the particularities of this technology and its applications was recently published in a special edition of the Journal of Aerosol Sciences [1]. Even though EHDA is already applied in many different industrial processes, there are not many controlling tools commercially available which can be used to remotely operate the system as well as identify some spray characteristics, e.g. droplet size, operational mode, droplet production ratio. The AECTion project proposes the development of an innovative controlling system based on the electrospray current, signal processing & control and artificial intelligence to build a non-visual tool to control and characterize EHDA processes.
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