Abstract：
An influential model of spatial attention postulates three main attention-orienting mechanisms: disengagement, shifting, and engagement. Early research linked disengagement deficits with superior parietal damage, regardless of hemisphere or presence of spatial neglect. Subsequent studies supported the involvement of more ventral parietal regions, especially in the right hemisphere, and linked spatial neglect to deficient disengagement from ipsilateral cues. However, previous lesion studies faced serious limitations, such as small sample sizes and the lack of brain-injured controls without neglect. Additionally, some studies employed symbolic cues or used long cue-target intervals, which may fail to reveal impaired disengagement. We here used a machine-learning approach to conduct lesion-symptom mapping (LSM) on 89 patients with focal cerebral lesions to the left (LH) or right (RH) cerebral hemisphere. A group of 54 healthy participants served as controls. The paradigm used to uncover disengagement deficits employed non-predictive cues presented in the visual periphery and at short cue-target intervals, targeting exogenous attention. The main factors of interest were group (healthy participants, LH, RH), target position (left, right hemifield) and cue validity (valid, invalid). LSM-analyses were performed on two indices: the validity effect, computed as the absolute difference between reaction times (RTs) following invalid compared to valid cues, and the disengagement deficit, determined by the difference between contralesional and ipsilesional validity effects. While LH patients showed general slowing of RTs to contralesional targets, only RH patients exhibited a disengagement deficit from ipsilesional cues. LSM associated the validity effect with a right lateral frontal cluster, which additionally affected subcortical white matter of the right arcuate fasciculus, the corticothalamic pathway, and the superior longitudinal fasciculus. In contrast, the disengagement deficit was related to damage involving the right temporoparietal junction. Thus, our results support the crucial role of right inferior parietal and posterior temporal regions for attentional disengagement, but also emphasize the importance of lateral frontal regions, for the reorienting of attention.
摘要：
一个有影响力的空间注意力模型假设三种主要的注意力导向机制：脱离接触，shifting,和订婚。早期研究将脱离接触缺陷与上顶叶损伤联系起来，无论半球或存在空间忽视。随后的研究支持更多腹侧顶区的参与，尤其是在右半球，并将空间忽视与同侧线索的缺乏脱离联系起来。然而,以前的病变研究面临严重的局限性，例如小样本量和没有忽视的脑损伤控制。此外,一些研究采用象征性提示或使用长提示-目标间隔，这可能无法揭示受损的脱离接触。我们在这里使用机器学习方法对89例局灶性脑部病变的左侧（LH）或右侧（RH）大脑半球进行病变症状映射（LSM）。一组54名健康参与者作为对照。用于发现脱离接触缺陷的范式采用了视觉外围和短提示目标间隔的非预测性提示，针对外源性注意力。感兴趣的主要因素是群体(健康参与者，LH,RH),目标位置(左,右半场)和提示有效性(有效，无效)。对两个指标进行了LSM分析：有效性效应，计算为无效后的反应时间(RT)与有效线索之间的绝对差，和脱离接触赤字，由对比效度和同义效度之间的差异决定。虽然LH患者显示RTs普遍减慢至对照目标，只有RH患者从病患线索中表现出脱离缺陷。LSM将有效性效应与右侧额叶聚类相关联，还影响了右弓状束的皮质下白质，皮质丘脑途径，和上纵束。相比之下,脱离接触缺陷与涉及右颞顶交界处的损害有关。因此，我们的结果支持右下顶区和后颞区对注意力脱离的关键作用，但也强调了外侧额叶区域的重要性，重新定位注意力。
