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  • 1
    Electronic Resource
    Electronic Resource
    Modulation of oscillatory brain activity and evoked potentials in a repetition priming task in the human EEG (2004)
    Oxford, UK : Blackwell Science Ltd
    European journal of neuroscience 19 (2004), S. 0 
    Details
    ISSN: 1460-9568
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Medicine
    Notes: Cortical object representations seem to require the formation of neural cell assemblies. The physiological correlate of cell assembly activity may be seen in synchronized neural activity in the gamma band range. The improvement in perceiving and identifying an object by experience is commonly referred to as repetition priming. One possible neural mechanism for repetition priming is ‘repetition suppression’ within a cell assembly coding the stimulus. The present electroencephalogram study was designed to investigate oscillatory brain activity when line drawings of concrete objects were repeated either immediately after a first presentation or after intervening a number of different stimuli. Results showed a broad posterior distribution of induced gamma band responses (GBRs) after the initial picture presentation. Repeated presentations of the same picture led to a significant decrease of induced gamma power. Furthermore, repeated presentations of the same object resulted in a decrease in phase synchrony between distant electrode sites. No significant repetition effects were found in the alpha or beta frequency range. The event-related potential (ERP), which was also modulated by priming, showed a different scalp distribution compared with induced GBRs. In addition, ERP repetition effects decayed at larger intervals between initial and repeated presentations, whereas induced GBRs were not modulated as a function of stimulus lag. We concluded that the decrease in amplitude of induced GBRs and the reduction of gamma phase synchrony between pairs of electrodes after repeated picture presentations might be linked to a ‘sharpening’ mechanism within a cell assembly representing an object.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1111/j.0953-816X.2004.03176.x
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  • 2
    Electronic Resource
    Electronic Resource
    Automated knowledge acquisition for strategic knowledge (1989)
    Springer
    Machine learning 4 (1989), S. 293-336 
    Details
    ISSN: 0885-6125
    Keywords: knowledge acquisition ; knowledge engineering ; human-computer interaction ; strategic knowledge ; knowledge representation
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science
    Notes: Abstract Strategic knowledge is used by an agent to decide what action to perform next, where actions have consequences external to the agent. This article presents a computer-mediated method for acquiring strategic knowledge. The general knowledge acquisition problem and the special difficulties of acquiring strategic knowledge are analyzed in terms of representation mismatch: the difference between the form in which knowledge is available from the world and the form required for knowledge systems. ASK is an interactive knowledge acquisition tool that elicits strategic knowledge from people in the form of justifications for action choices and generates strategy rules that operationalize and generalize the expert's advice. The basic approach is demonstrated with a human-computer dialog in which ASK acquires strategic knowledge for medical diagnosis and treatment. The rationale for and consequences of specific design decisions in ASK are analyzed, and the scope of applicability and limitations of the approach are assessed. The paper concludes by discussing the contribution of knowledge representation to automated knowledge acquisition.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1007/BF00130716
    Library Location Call Number Volume/Issue/Year Availability
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    Paper (German National Licenses)
    Fulltext
  • 3
    Electronic Resource
    Electronic Resource
    Automated Knowledge Acquisition for Strategic Knowledge (1989)
    Springer
    Machine learning 4 (1989), S. 293-336 
    Details
    ISSN: 0885-6125
    Keywords: knowledge acquisition ; knowledge engineering ; human–computer interaction ; strategic knowledge ; knowledge representation
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science
    Notes: Abstract Strategic knowledge is used by an agent to decide what action to perform next, where actions have consequences external to the agent. This article presents a computer-mediated method for acquiring strategic knowledge. The general knowledge acquisition problem and the special difficulties of acquiring strategic knowledge are analyzed in terms of representation mismatch: the difference between the form in which knowledge is available from the world and the form required for knowledge systems. ASK is an interactive knowledge acquisition tool that elicits strategic knowledge from people in the form of justifications for action choices and generates strategy rules that operationalize and generalize the expert's advice. The basic approach is demonstrated with a human–computer dialog in which ASK acquires strategic knowledge for medical diagnosis and treatment. The rationale for and consequences of specific design decisions in ASK are analyzed, and the scope of applicability and limitations of the approach are assessed. The paper concludes by discussing the contribution of knowledge representation to automated knowledge acquisition.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1023/A:1022654722798
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
    Paper (German National Licenses)
    Fulltext
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