Bridging the gap between physiology and behavior: evidence from the sSoTS model of human visual attention.

Bridging the gap between physiology and behavior: evidence from the sSoTS model of human visual attention.
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弥合生理学和行为之间的差距:来自人类视觉注意力 sSoTS 模型的证据。

DOI:
10.1037/a0021868
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发表时间:
2011
影响因子:
5.4
通讯作者:
Mavritsaki E
Mavritsaki E
中科院分区:
心理学1区
文献类型:
--
作者:
Mavritsaki E

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我们提出的情况下,生物合理的神经网络建模在弥合生理和行为之间的差距的作用。我们认为,尖峰水平的网络可以允许神经系统的生理特性和紧急的“全系统”的性能之间的“垂直”翻译,使心理结果被模拟从实施网络,并从有关处理在神经水平的模拟作出推论。这些模型还强调了在其他方法中没有强调的特定因素(例如,与实时神经元处理相关的性能动态),并且可以根据经验进行测试。我们说明了我们的论点,从神经层次的模型,选择刺激的偏见竞争。我们发现,一个有偏见的竞争动力学模型可以模拟从单细胞活动的生理研究(研究1)到人类视觉搜索中的全系统行为(研究2)的数据,同时还可以捕获中间水平的影响,包括神经损伤后的性能崩溃(研究3)和大脑成像数据(研究4)。我们还表明,在每个分析水平,新的预测可以从生物学上合理的参数,我们继续测试(研究5)。我们认为,至少对于研究视觉注意力的动态,这种方法有效地将单细胞与心理数据联系起来。(PsycInfo数据库记录(c)2020阿帕,保留所有权利)
We present the case for a role of biologically plausible neural network modeling in bridging the gap between physiology and behavior. We argue that spiking-level networks can allow “vertical” translation between physiological properties of neural systems and emergent “whole-system” performance—enabling psychological results to be simulated from implemented networks and also inferences to be made from simulations concerning processing at a neural level. These models also emphasize particular factors (eg, the dynamics of performance in relation to real-time neuronal processing) that are not highlighted in other approaches and that can be tested empirically. We illustrate our argument from neural-level models that select stimuli by biased competition. We show that a model with biased competition dynamics can simulate data ranging from physiological studies of single-cell activity (Study 1) to whole-system behavior in human visual search (Study 2), while also capturing effects at an intermediate level, including performance breakdown after neural lesion (Study 3) and data from brain imaging (Study 4). We also show that, at each level of analysis, novel predictions can be derived from the biologically plausible parameters adopted, which we proceed to test (Study 5). We argue that, at least for studying the dynamics of visual attention, the approach productively links single-cell to psychological data.(PsycInfo Database Record (c) 2020 APA, all rights reserved)
注意对象内和对象间的空间表示:用于视觉选择的多个站点
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