Adaptive allocation of attentional gain

描述（由申请人提供）：人类感觉系统不断受到远远超过其处理能力的输入的轰炸。因此，注意力机制已经进化，使得可用的能力只用于编码环境中最显著和行为相关的刺激。反过来，最重要的刺激支配着知觉意识，并有特权访问记忆存储和神经机制，这些机制控制着如何最好地与外部物体互动的决定。在这个提议中，我们将使用视觉系统作为模型来理解选择性注意力影响感知、工作记忆和感觉运动决策的计算所涉及的基本脑行为过程。此外，我们将开发和采用新的方法，使用功能磁共振成像来非侵入性地研究注意力调制和感觉系统的信息编码能力，符合NIMH的战略目标，开发新的工具和方法，以了解神经细胞群体如何在大脑区域内和之间共同工作。 传统的解释认为，注意力的作用是放大重要刺激引起的神经反应，使刺激更容易被感知。这个一般框架是直观的，并已成功地指导了三十多年的实证研究。然而，最近的理论研究表明，注意力不应该仅仅增加神经元对相关刺激的增益。相反，注意力应该以更动态的方式调节感觉神经元的活动，以最大限度地提高成功完成特定感知任务的概率。通常情况下，这需要增强对视野中不存在的刺激最敏感的神经元的活动，因为这些神经元携带更多关于相似项目之间非常困难的区分的信息（例如，当放射科医生在低质量X射线图像中搜索癌性肿块时）。最近的实证研究支持这一总体框架，并进一步提出了一种有趣的可能性，即注意力最优性的个体差异可以预测困难辨别的整体表现以及通过实践（学习）提高困难辨别的能力。在这里，我们将批判性地评估这一新的理论观点，我们还将探讨个体之间的注意力差异如何影响短期记忆的精度和简单决策过程的效率。总的来说，我们的目标是提供对注意机制运作的见解，以便我们能够更精确地描述系统应该如何理想地运作。反过来，这将极大地提高我们隔离注意力处理的特定方面的能力，这些方面有时会出错，从而使临床环境中更有针对性的诊断和干预成为可能。

DESCRIPTION (provided by applicant): Human sensory systems are continuously bombarded with far more input than they can process. As a result, attentional mechanisms have evolved so that available capacity is dedicated to encoding only the most salient and behaviorally relevant stimuli in the environment. In turn, the most important stimuli dominate perceptual awareness and have privileged access to memory stores and to the neural mechanisms that control decisions about how to best interact with external objects. In this proposal, we will use the visual system as a model to understand the basic brain-behavior processes involved in selective attention influence perception, working memory, and the computation of sensorimotor decisions. In addition, we will develop and employ new methods that use fMRI to non-invasively study attentional modulations and the information encoding capacity of sensory systems, in line with the strategic aim of the NIMH to develop novel tools and methodologies for understanding how populations of neural cells work together within and between brain regions. Traditional accounts hold that attention operates to magnify the neural response evoked by important stimuli, which makes a stimulus easier to perceive. This general framework is intuitive, and has been successfully guiding empirical studies for more than three decades. However, recent theoretical work suggests that attention should not simply increase the gain of neurons tuned to a relevant stimulus. Instead, attention should modulate the activity of sensory neurons in a more dynamic manner in order to maximize the probability that a specific perceptual task will be successfully completed. Often times, this counterintuitively requires enhancing the activity of neurons that are most responsive to stimuli that are not physically present in the visual field, because these neurons carry more information about very difficult discriminations between similar items (e.g. when a radiologist searches for a cancerous mass in a low-quality x-ray image). Recent empirical studies support this general framework, and further raise the intriguing possibility that individual differences in the optimality of attention can predict overall performance on difficult discriminations as well as the ability to improve on difficult discriminations with practice (learning). Here, we will critically evaluate this new theoretical perspective, and we will also explore how differences in attention across individuals can influence the precision of short-term memory and the efficiency of simple decision making processes. Collectively, our goal is to provide insights into the operation of attentional mechanisms so that we can more precisely characterize how the system should ideally operate. In turn, this should dramatically improve our ability to isolate specific aspects of attentional processing that can sometimes go awry, thereby enabling more targeted diagnoses and interventions in clinical settings.