LEADER 03926oam 2200637 450 001 9910137097103321 005 20230621135711.0 010 $a9782889196135 035 $a(CKB)3710000000824707 035 $a(oapen)https://directory.doabooks.org/handle/20.500.12854/61794 035 $a(EXLCZ)993710000000824707 100 $a20191103h20152015 fy| 0 101 0 $aeng 135 $aur||#---||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 00$aUsing neurophysiological signals that reflect cognitive or affective state /$fedited by: Anne-Marie Brouwer, Thorsten O. Zander and Jan B. F. van Erp 210 $cFrontiers Media SA$d2015 210 1$a[Lausanne, Switzerland] :$cFrontiers Media SA,$d2015. 210 4$dİ2015 215 $a1 online resource (314 pages) $cillustrations; digital file(s) 225 1 $aFrontiers Research Topics 225 0 $aFrontiers in Neuroscience 311 08$aPrint version: 2-88919-613-5 320 $aIncludes bibliographical references. 330 $aWhat can we learn from spontaneously occurring brain and other physiological signals about an individual's cognitive and affective state and how can we make use of this information? One line of research that is actively involved with this question is Passive Brain-Computer-Interfaces (BCI). To date most BCIs are aimed at assisting patients for whom brain signals could form an alternative output channel as opposed to more common human output channels, like speech and moving the hands. However, brain signals (possibly in combination with other physiological signals) also form an output channel above and beyond the more usual ones: they can potentially provide continuous, online information about an individual's cognitive and affective state without the need of conscious or effortful communication. The provided information could be used in a number of ways. Examples include monitoring cognitive workload through EEG and skin conductance for adaptive automation or using ERPs in response to errors to correct for a behavioral response. While Passive BCIs make use of online (neuro)physiological responses and close the interaction cycle between a user and a computer system, (neuro)physiological responses can also be used in an offline fashion. Examples of this include detecting amygdala responses for neuromarketing, and measuring EEG and pupil dilation as indicators of mental effort for optimizing information systems. The described field of applied (neuro)physiology can strongly benefit from high quality scientific studies that control for confounding factors and use proper comparison conditions. Another area of relevance is ethics, ranging from dubious product claims, acceptance of the technology by the general public, privacy of users, to possible effects that these kinds of applications may have on society as a whole. 410 0$aFrontiers research topics. 606 $aNeurophysiology 606 $aNeuropsychiatry 606 $aBrain-computer interfaces 606 $aNeurosciences 610 $aBrain-computer interface 610 $acognitive state 610 $aEEG 610 $aaffective state 610 $aphysiological computing 610 $amental state 610 $aapplied neuroscience 610 $aPsychophysiology 610 $aneuroergonomics 610 $aNeurophysiology 615 0$aNeurophysiology. 615 0$aNeuropsychiatry. 615 0$aBrain-computer interfaces. 615 0$aNeurosciences. 676 $a612.82 700 $aAnne-Marie Brouwer$4auth$01364353 702 $aBrouwer$b Anne-Marie 702 $aZander$b Thorsten O. 702 $aErp$b Jan B. F. van$f1969- 801 0$bUkMaJRU 906 $aBOOK 912 $a9910137097103321 996 $aUsing neurophysiological signals that reflect cognitive or affective state$93385553 997 $aUNINA