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{ "item_title" : "Quantifying Human Information Processing", "item_author" : [" James P. Bliss", "Walter R. Boot", "Daniel Caggiano "], "item_description" : "Rapid advances in IT that allow complex information to be presented in high volume and density are challenging human ability to absorb and analyze data as never before. Designing technologies and systems to provide optimal sensory information to human users will be increasingly important. But to do this, quantitative relationships between brain behavior at a molecular level and observable human behavior must be better identified. This was previously considered to be a futuristic, and somewhat unrealistic, goal, however, recent advances in cognitive neuroscience have provided new opportunities for researchers.Refinements in imaging technology and simulation tools, and the learning yielded from them, provided the Quantifying Human Information Processing (QHIP) research teams strong starting points from which to further assess the ability to quantify human information processing. Led by experts in psychology, cognitive science, and information processing, among other fields, researchers sought to quantify the information flow in the nervous system, the limits of that flow, and how it is affected by emotions. The QHIP effort looked at specific aspects of the brain's information processing ability including measuring task-related and unrelated thought, assessing mental workload, and finding optimal information processing. The researchers found important indicators of both the capacity and limits of the human brain, and offer new ways to think about the brain. This work is a valuable contribution to the fields of psychology, neuroscience, and cognition, and will serve as a resource for human factors engineers designing the next generation of information, safety, analysis, and control systems because it starts to answer how to maximize information processing without overloading the central nervous system.", "item_img_path" : "https://covers3.booksamillion.com/covers/bam/0/73/911/201/0739112015_b.jpg", "price_data" : { "retail_price" : "130.00", "online_price" : "130.00", "our_price" : "130.00", "club_price" : "130.00", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }
Quantifying Human Information Processing|James P. Bliss

Quantifying Human Information Processing

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Overview

Rapid advances in IT that allow complex information to be presented in high volume and density are challenging human ability to absorb and analyze data as never before. Designing technologies and systems to provide optimal sensory information to human users will be increasingly important. But to do this, quantitative relationships between brain behavior at a molecular level and observable human behavior must be better identified. This was previously considered to be a futuristic, and somewhat unrealistic, goal, however, recent advances in cognitive neuroscience have provided new opportunities for researchers.

Refinements in imaging technology and simulation tools, and the learning yielded from them, provided the Quantifying Human Information Processing (QHIP) research teams strong starting points from which to further assess the ability to quantify human information processing. Led by experts in psychology, cognitive science, and information processing, among other fields, researchers sought to quantify the information flow in the nervous system, the limits of that flow, and how it is affected by emotions. The QHIP effort looked at specific aspects of the brain's information processing ability including measuring task-related and unrelated thought, assessing mental workload, and finding optimal information processing. The researchers found important indicators of both the capacity and limits of the human brain, and offer new ways to think about the brain. This work is a valuable contribution to the fields of psychology, neuroscience, and cognition, and will serve as a resource for human factors engineers designing the next generation of information, safety, analysis, and control systems because it starts to answer how to maximize information processing without overloading the central nervous system.

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Details

  • ISBN-13: 9780739112014
  • ISBN-10: 0739112015
  • Publisher: Jason Aronson
  • Publish Date: June 2005
  • Dimensions: 8.99 x 6.32 x 0.92 inches
  • Shipping Weight: 1.29 pounds
  • Page Count: 264

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