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Evaluating the performance of the visual half field paradigm as a screening tool to detect right hemispheric language dominance.
Laterality ( IF 2.167 ) Pub Date : 2020-11-01 , DOI: 10.1080/1357650x.2020.1854279
Robin Gerrits 1 , Pieter De Clercq 2 , Helena Verhelst 1 , Guy Vingerhoets 1
Affiliation  

Language is among the most studied functional asymmetries, yet little is known about right hemispheric language dominance. Because of its low prevalence, including a big sample of individuals with this variant of brain organization implies testing large groups, which may not be feasible when using expensive techniques. One solution involves screening a large sample using a cost-efficient method and next inviting only those participants flagged as potentially right dominant for follow-up investigation. The behavioural visual half field paradigm has previously been validated and successfully applied in this manner. We report a large-scale visual half field screening performed in 315 left-handers to detect such individuals for subsequent MRI scanning. Of 38 cases selected as probably right language dominant based on a left visual half field advantage (>20 ms), 22 (58%) were confirmed by language fMRI to be rightward lateralized. This study also explored means to improve the predictive performance of the visual half field task. While we found its performance depended strongly on the chosen cut-off, overall, reaction time criteria resulted in higher true positive rates, while those based on accuracy led to superior positive predictive values. The most optimal strategy, however, may involve combining criteria considering both accuracy and reaction time.

中文翻译:

评估视觉半场范式作为检测右半球语言优势的筛选工具的性能。

语言是研究最多的功能不对称之一,但对右半球语言的主导地位知之甚少。由于它的患病率低,因此包括大量具有这种大脑组织变异的个体样本意味着要测试大量的群体,这在使用昂贵的技术时可能不可行。一种解决方案涉及使用经济高效的方法筛选大样本,然后仅邀请那些被标记为潜在正确主体的参与者进行后续调查。行为视觉半场范式以前已经通过验证并成功地以这种方式应用。我们报告了在315个左撇子中进行的大规模视觉半场筛查,以检测此类个体以进行后续MRI扫描。根据左视野半场优势(> 20 ms)选择38例可能是右语言优势的病例,其中22例(58%)被语言功能磁共振成像证实为右偏。这项研究还探索了改善视觉半场任务的预测性能的方法。虽然我们发现其性能在很大程度上取决于所选的临界值,但总的来说,反应时间标准会导致较高的真实阳性率,而基于准确性的标准会导致较高的阳性预测值。然而,最优化的策略可能涉及考虑准确性和反应时间的标准组合。虽然我们发现其性能在很大程度上取决于所选的临界值,但总的来说,反应时间标准会导致较高的真实阳性率,而基于准确性的标准会导致较高的阳性预测值。然而,最优化的策略可能涉及考虑准确性和反应时间的标准组合。虽然我们发现其性能在很大程度上取决于所选的临界值,但总的来说,反应时间标准会导致较高的真实阳性率,而基于准确性的标准会导致较高的阳性预测值。然而,最优化的策略可能涉及考虑准确性和反应时间的标准组合。
更新日期:2020-11-01
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