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视觉搜索任务中上下文依赖特征联结学习的神经关联

Neural correlates of context-dependent feature conjunction learning in visual search tasks.

作者信息

Reavis Eric A, Frank Sebastian M, Greenlee Mark W, Tse Peter U

机构信息

Department of Psychological and Brain Sciences, Dartmouth College, Hanover, New Hampshire, USA.

Institute of Experimental Psychology, University of Regensburg, Regensburg, Germany.

出版信息

Hum Brain Mapp. 2016 Jun;37(6):2319-30. doi: 10.1002/hbm.23176. Epub 2016 Mar 11.

Abstract

Many perceptual learning experiments show that repeated exposure to a basic visual feature such as a specific orientation or spatial frequency can modify perception of that feature, and that those perceptual changes are associated with changes in neural tuning early in visual processing. Such perceptual learning effects thus exert a bottom-up influence on subsequent stimulus processing, independent of task-demands or endogenous influences (e.g., volitional attention). However, it is unclear whether such bottom-up changes in perception can occur as more complex stimuli such as conjunctions of visual features are learned. It is not known whether changes in the efficiency with which people learn to process feature conjunctions in a task (e.g., visual search) reflect true bottom-up perceptual learning versus top-down, task-related learning (e.g., learning better control of endogenous attention). Here we show that feature conjunction learning in visual search leads to bottom-up changes in stimulus processing. First, using fMRI, we demonstrate that conjunction learning in visual search has a distinct neural signature: an increase in target-evoked activity relative to distractor-evoked activity (i.e., a relative increase in target salience). Second, we demonstrate that after learning, this neural signature is still evident even when participants passively view learned stimuli while performing an unrelated, attention-demanding task. This suggests that conjunction learning results in altered bottom-up perceptual processing of the learned conjunction stimuli (i.e., a perceptual change independent of the task). We further show that the acquired change in target-evoked activity is contextually dependent on the presence of distractors, suggesting that search array Gestalts are learned. Hum Brain Mapp 37:2319-2330, 2016. © 2016 Wiley Periodicals, Inc.

摘要

许多知觉学习实验表明,反复接触诸如特定方向或空间频率等基本视觉特征,能够改变对该特征的感知,并且这些知觉变化与视觉处理早期神经调谐的变化相关。因此,这种知觉学习效应会对后续的刺激处理产生自下而上的影响,独立于任务需求或内源性影响(例如,意志性注意)。然而,尚不清楚当学习诸如视觉特征组合等更复杂的刺激时,这种自下而上的知觉变化是否会发生。人们在一项任务(例如视觉搜索)中学习处理特征组合的效率变化,是反映了真正的自下而上的知觉学习,还是自上而下的、与任务相关的学习(例如,学习更好地控制内源性注意),目前尚不清楚。在这里,我们表明视觉搜索中的特征组合学习会导致刺激处理的自下而上的变化。首先,使用功能磁共振成像,我们证明视觉搜索中的组合学习具有独特的神经特征:相对于干扰物诱发的活动,目标诱发的活动增加(即目标显著性的相对增加)。其次,我们证明学习后,即使参与者在执行一项无关的、需要注意力的任务时被动地观看所学刺激,这种神经特征仍然明显。这表明组合学习导致了对所学组合刺激的自下而上的知觉处理发生改变(即与任务无关的知觉变化)。我们进一步表明,目标诱发活动的获得性变化在情境上依赖于干扰物的存在,这表明搜索阵列的格式塔被学习到了。《人类大脑图谱》37:2319 - 2330, 2016。© 2016威利期刊公司。

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本文引用的文献

1
Caudate nucleus reactivity predicts perceptual learning rate for visual feature conjunctions.
Neuroimage. 2015 Apr 15;110:171-81. doi: 10.1016/j.neuroimage.2015.01.051. Epub 2015 Jan 31.
2
Pretraining Cortical Thickness Predicts Subsequent Perceptual Learning Rate in a Visual Search Task.
Cereb Cortex. 2016 Mar;26(3):1211-1220. doi: 10.1093/cercor/bhu309. Epub 2015 Jan 9.
3
Context-dependent savings in procedural category learning.
Brain Cogn. 2014 Dec;92C:1-10. doi: 10.1016/j.bandc.2014.09.008. Epub 2014 Oct 17.
4
Neural mechanisms of feature conjunction learning: enduring changes in occipital cortex after a week of training.
Hum Brain Mapp. 2014 Apr;35(4):1201-11. doi: 10.1002/hbm.22245. Epub 2013 Feb 18.
5
Decoding reveals plasticity in V3A as a result of motion perceptual learning.
PLoS One. 2012;7(8):e44003. doi: 10.1371/journal.pone.0044003. Epub 2012 Aug 28.
6
Advances in visual perceptual learning and plasticity.
Nat Rev Neurosci. 2010 Jan;11(1):53-60. doi: 10.1038/nrn2737. Epub 2009 Dec 2.
7
Experience can change distinct size-weight priors engaged in lifting objects and judging their weights.
Curr Biol. 2008 Nov 25;18(22):1742-7. doi: 10.1016/j.cub.2008.09.042.
8
Different dynamics of performance and brain activation in the time course of perceptual learning.
Neuron. 2008 Mar 27;57(6):827-33. doi: 10.1016/j.neuron.2008.02.034.
9
Attentional load modulates responses of human primary visual cortex to invisible stimuli.
Curr Biol. 2007 Mar 20;17(6):509-13. doi: 10.1016/j.cub.2007.01.070. Epub 2007 Mar 8.
10
Learning strengthens the response of primary visual cortex to simple patterns.
Curr Biol. 2004 Apr 6;14(7):573-8. doi: 10.1016/j.cub.2004.03.032.

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