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The neural bases of task proficiency and dual-tasking: Escaping the frontal bottleneck

The neural bases of task proficiency and dual-tasking: Escaping the frontal bottleneck
任务熟练度和双重任务的神经基础:摆脱额叶瓶颈
批准号:
1232530
负责人:
Maximilian Riesenhuber
金额:
$70.59万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2012
资助国家:
美国
项目状态:
已结题
起止时间:
2012-09-01 至 2018-08-31

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中文摘要
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英文摘要
One of the most impressive aspects of human cognition is its ability to, through practice, convert effortful tasks to those that can be performed with little effort, and even in parallel with other, attention-demanding tasks. The recent proliferation of technologies permitting constant engagement in our culture has made multitasking increasingly prevalent, giving rise to new policy challenges as people's attempts at multitasking exceed their cognitive capabilities, such as when texting while driving. A better understanding of the brain's capabilities and limitations to automate tasks is therefore highly desirable. Yet, the neural bases of automaticity and multitasking are still poorly understood, leading to substantial disagreement about the brain's multitasking capabilities. In particular, while there is broad consensus that learning new tasks is associated with the development of task-selective circuits in the front of the brain which are selectively activated or suppressed depending on the individual's attentional focus, several experiments have shown that this architecture can create a cognitive "bottleneck" in situations when more than one task needs to be executed at the same time. Dr. Maximilian Riesenhuber and his team at Georgetown University are testing the key hypothesis that under certain conditions, familiar tasks can be "offloaded" to circuits in the back of the brain, thus freeing up the frontal system to simultaneously perform additional, attention-demanding tasks. To test this hypothesis, the project will use sophisticated behavioral training paradigms to enable participants to perform more than one task in parallel, and then use a combination of advanced functional magnetic resonance imaging (fMRI) and electroencephalographic (EEG) techniques to track how the brain learns to enable multitasking. The study will advance our understanding of the mechanisms underlying the brain's ability to automatize and parallelize task execution, essential in the face of the increasing pressures to multitask in today's culture. The results will also be relevant for a range of societal and medical challenges. For instance, deficits in multitasking and task switching have been associated with schizophrenia and attention deficit hyperactivity disorder. In addition, it is being increasingly appreciated that automaticity itself can be associated with negative consequences, as automatic processes can reduce flexibility in responding due to a lack of conscious awareness and decreased control. For instance, a challenge in treating drug addiction is that many maladaptive behaviors associated with drug abuse become automatized. Even when associated with high performance, automatic task execution can be problematic in domains in which accountability is critical, such as in legal or medical decision-making. Understanding how the brain automatizes tasks is a key stepping stone in making progress in these areas.
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Architecture and plasticity of auditory lexical representations in the human brain
  • 批准号:
    1756313
  • 项目类别:
    Standard Grant
  • 资助金额:
    $65.2万
  • 财政年份:
    2018
  • 负责人:
    Maximilian Riesenhuber
  • 依托单位:
Collaborative Research: Using Somatosensory Speech And Non-Speech Categories To Test The Brain's General Principles Of Perceptual Learning
  • 批准号:
    1439338
  • 项目类别:
    Standard Grant
  • 资助金额:
    $61.64万
  • 财政年份:
    2014
  • 负责人:
    Maximilian Riesenhuber
  • 依托单位:
Plasticity of Orthographic and Semantic Representations in the Human Brain
  • 批准号:
    1026934
  • 项目类别:
    Continuing Grant
  • 资助金额:
    $65.07万
  • 财政年份:
    2010
  • 负责人:
    Maximilian Riesenhuber
  • 依托单位:
The Interaction of Bottom-up and Top-down Information in Human Auditory Learning and Object Recognition
  • 批准号:
    0749986
  • 项目类别:
    Standard Grant
  • 资助金额:
    $58.34万
  • 财政年份:
    2008
  • 负责人:
    Maximilian Riesenhuber
  • 依托单位:
国内基金
海外基金
量子无偏基的理论及应用研究
  • 批准号:
    10704001
  • 项目类别:
    青年科学基金项目
  • 资助金额:
    19.0万元
  • 批准年份:
    2007
  • 负责人:
    杨名
  • 依托单位: