What do you say? An investigation of how lesions cause language deficits in post-stroke

中风随时可能发生在任何人身上，包括新生儿和儿童。当大脑某个区域的血液供应受到影响，导致脑细胞死亡时，就会发生中风。脑细胞的丧失可能导致某一领域所特有的功能缺陷。例如，大约三分之一的中风幸存者在语言理解和/或语言产生方面存在缺陷，这种情况被称为失语症。失语症被认为是由中风后背侧和/或腹侧语言通路的损害引起的(Weiller等人。2011年；希科克和波佩尔，2007年；希科克和波佩尔，2000年；埃格特，1997年)。失语症对患者具有毁灭性的后果，因为无法与所爱的人和更广泛的社区进行交流和互动，同时还会付出相当大的社会代价。我们知道，中风后患者恢复语言能力的能力取决于大脑损伤的总比例，支持语言的区域是否受到损伤，以及初始症状的强度(Price等人)。2010)。此外，使用数据驱动的方法，研究表明中风后康复比之前认为的更加系统化和可预测(Hope等人)。2018年；霍普等人。2017年；Seghier等人。2014年；霍普等人。2013年；Seghier等人。2012年；Saur等人。2010年；Blasi等人。2002年；Musso等人。1999年)。然而，如果没有一个机械性的、过程级的描述，说明语言技能是如何在健康的大脑中实施的，我们就无法理解当这些技能因中风而受损时，哪里出了问题(因此，考虑如何最好地解决它)。这一理解对于给患者提供准确的康复指征至关重要。因此，该项目旨在通过计算模型来调查病变损伤导致中风后失语症状的过程。计算模型是研究这一范式的合适框架，因为它将允许我们对正常行为进行建模，然后破坏模型，以更好地理解贝叶斯理论。这将解释病变损伤如何以及为什么会导致不同类型和严重程度的失语症。

A stroke can happen at any time to anyone, including new-borns and children. Stroke occurs when blood supply to an area in the brain is compromised, causing brain cells to die. Loss of brain cells can lead to deficits in functions for which an area specialised. For example, approximately a third of stroke survivors have deficits in speech comprehension and/or production, a condition referred to as aphasia. Aphasia is, thought to be, caused by lesions in dorsal and/or ventral language pathways post-stroke (Weiller, et al. 2011; Hickok and Poeppel, 2007; Hickok and Poeppel, 2000; Eggert, 1997). Aphasia has devastating consequences for the affected individual, due to inability to communicate and engage with loved ones and the wider community, alongside considerable societal cost.We know that the ability of a patient to recover their language capabilities post-stroke depends on the total proportion of damage to the brain, whether areas that support language have been damaged and the intensity of the initial symptoms (Price, et al. 2010). Additionally, using data-driven methods, research shows that post-stroke recovery is much more systematic and predictable than was previously thought (Hope, et al. 2018; Hope, et al. 2017; Seghier, et al. 2014; Hope et al. 2013; Seghier, et al. 2012; Saur, et al. 2010; Blasi, et al. 2002; Musso, et al. 1999). However, without a mechanistic, process-level account of how language skills are implemented in a healthy brain, we cannot understand what has gone wrong (and therefore, consider how best to resolve it) when those skills are impaired by stroke. This understanding is crucial for giving patients an accurate indication of recovery.Thus, the project aims to investigate the process by which lesion damage causes aphasic symptoms post-stroke using computational modelling. Computational modelling is an appropriate framework to study this paradigm since it will allow us to model both normal behaviour and then lesion the model to forge a better understanding if Bayesian. This will explain how and why lesion damage can cause different types and severity of aphasia.