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Resilience, Adaptability and System Safety
Published in David O'Hare, Introduction to Safety Science, 2022
As noted previously in this book, the development of cybernetics, with its emphasis on the importance of feedback in various kinds of systems, along with other advances in techniques for analysing network structures have greatly contributed to the development of general systems theory or systems science. Notably, the kind of explanations for phenomena used in systems science is typically broader than the narrower ‘cause and effect' chain of events in time that forms the backbone of explanation in conventional science. Many phenomena in systems resist such simple explanations. For example, the process of remembering information can be thought of as one of ‘spreading activation' across a network of nodes and linkages.23 The estimated 86 billion (give or take) neurons in the human brain constitute a vast network of interconnections.24
Development of skilled performance: An age-related perspective
Published in Diane L. Damos, Multiple-task performance, 2020
Arthur D. Fisk, Wendy A. Rogers
A lexical decision task consists of presenting two letter strings and requiring the subject to determine if they are both words (Meyer and Schvanaveldt, 1971). A variation of this task involves the presentation of a semantic prime followed by a letter string. (A prime activates information that is stored in long-term memory. Semantic priming refers to the presentation of some word which activates the semantic concepts associated with that word). The validity of the prime can be manipulated to enable cost-benefit analysis (Posner and Snyder, 1975). The semantic priming effects observed in lexical decision tasks (i.e., having just made a judgement about one word facilitates judgements about semantically related words) are often interpreted in terms of the automatic spreading activation which accompanies looking up a word in memory.
Panic attacks and anxiety disorders
Published in Herman Staudenmayer, Environmental Illness, 2018
Similar facilitating effects in reaction time have also been observed in word recognition tasks involving conceptual semantic representation in long-term memory. For example, the recognition reaction time that a string of letters was a word as opposed to a non-word was faster when the target word was preceded by another word which was semantically related (e.g., nurse preceded by doctor) compared to an unrelated pair (e.g., butter preceded by doctor). The observed effects are attributed to spreading activation of related concepts in memory networks (Schvaneveldt and Meyer, 1973). Neuroanatomical studies with PET have corroborated this hypothesis in that focusing attention on concepts in the same category showed a cortical activation pattern closer in anatomical proximity compared to categorically unrelated concepts (Spitzer et al., 1995). The spreading activation observed in word-recognition experiments is consistent with more speculative hypotheses that there are distinct neurological correlates for complex conceptual representations of traumatic experiences. A PET study by Rauch et al. (1996) showed that when people were exposed to individualized, script-driven imagery of their trauma, there was more activation in right hemisphere areas involved with emotional arousal as well as in the right visual association cortex. Concurrently, there was also less activation in Broca’s area located in the left hemisphere, suggesting an inhibition to verbalizing the experience.
Associative activation during interrupted task performance: a mixed methods approach to understanding the overall quality effects of interruptions
Published in Theoretical Issues in Ergonomics Science, 2018
Nicole E. Werner, Cyrus K. Foroughi, Carryl Baldwin, Robert Youmans, Deborah A. Boehm-Davis
Spreading activation is a model of semantic processing based on associative processes in which nodes or concepts in the semantic network within memory are activated based on their levels of association with other concepts in the semantic network (Collins and Loftus, 1975). The semantic network is comprised of a complex set of associations between nodes connected by weighted associative pathways.