The Human Brain and Information Science: Lessons from Popular Neuroscience
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Insights from the recent wealth of popular books on neuroscience areoffered to suggest a strengthening of theory in information science. Information theory has traditionally neglected the human dimension infavour of ‘scientific’ theory often derived from the Shannon-Weaver model. Neuroscientists argue in excitingly fresh ways from the evidence of casestudies, non-intrusive experimentation and the measurements that can beobtained from technologies that include electroencephalography, positronemission tomography (PET), functional magnetic resonance imaging(fMRI), and magnetoencephalography (MEG). The way in which thefindings of neuroscience intersect with ideas such as those of Kahnemanon fast and slow thinking and Csikszentmihalyi on flow, is tentativelyexplored as lines of connection with information science. It is arguedthat the beginnings of a theoretical underpinning for current web-basedinformation searching in relation to established information retrievalmethods can be drawn from this.
Abstract
Insights from the recent wealth of popular books on neuroscience areoffered to suggest a strengthening of theory in information science. Information theory has traditionally neglected the human dimension infavour of ‘scientific’ theory often derived from the Shannon-Weaver model. Neuroscientists argue in excitingly fresh ways from the evidence of casestudies, non-intrusive experimentation and the measurements that can beobtained from technologies that include electroencephalography, positronemission tomography (PET), functional magnetic resonance imaging(fMRI), and magnetoencephalography (MEG). The way in which thefindings of neuroscience intersect with ideas such as those of Kahnemanon fast and slow thinking and Csikszentmihalyi on flow, is tentativelyexplored as lines of connection with information science. It is arguedthat the beginnings of a theoretical underpinning for current web-basedinformation searching in relation to established information retrievalmethods can be drawn from this.
참고문헌 (28)
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