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Relating constructs of attention and working memory to social withdrawal in Alzheimer’s disease and schizophrenia: issues regarding paradigm selection
Neuroscience & Biobehavioral Reviews ( IF 7.5 ) Pub Date : 2018-11-03 , DOI: 10.1016/j.neubiorev.2018.09.025
Gary Gilmour , Stefano Porcelli , Valérie Bertaina-Anglade , Estibaliz Arce , Juergen Dukart , Anja Hayen , Antonio Lobo , Raul Lopez-Anton , Emilio Merlo Pich , Darrel J. Pemberton , Martha N. Havenith , Jeffrey C. Glennon , Brian T. Harel , Gerard Dawson , Hugh Marston , Rouba Kozak , Alessandro Serretti

Central nervous system diseases are not currently diagnosed based on knowledge of biological mechanisms underlying their symptoms. Greater understanding may be offered through an agnostic approach to traditional disease categories, where learning more about shared biological mechanisms across conditions could potentially reclassify sub-groups of patients to allow realisation of more effective treatments. This review represents the output of the collaborative group “PRISM”, tasked with considering assay choices for assessment of attention and working memory in a transdiagnostic cohort of Alzheimer’s disease and schizophrenia patients exhibiting symptomatic spectra of social withdrawal. A multidimensional analysis of this nature has not been previously attempted. Nominated assays (continuous performance test III, attention network test, digit symbol substitution, N-back, complex span, spatial navigation in a virtual environment) reflected a necessary compromise between the need for broad assessment of the neuropsychological constructs in question with several pragmatic criteria: patient burden, compatibility with neurophysiologic measures and availability of preclinical homologues.



中文翻译:

将注意力和工作记忆的结构与阿尔茨海默氏病和精神分裂症的社交退缩相关:范式选择问题

目前,中枢神经系统疾病尚未根据其症状背后的生物学机制知识进行诊断。可以通过对传统疾病类别的不可知论方法来获得更多的了解,在这种方法中,了解更多有关跨病状的共享生物学机制的信息,有可能对患者的亚组进行重新分类,从而实现更有效的治疗。这篇综述代表了“ PRISM”协作小组的成果,该小组的任务是考虑对阿尔茨海默氏病和精神分裂症患者表现出社交退缩症状谱图的经转诊人群评估注意力和工作记忆的试验选择。以前从未尝试过这种性质的多维分析。提名的测定(连续性能测试III,注意力网络测试,

更新日期:2018-11-03
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