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    • Interrogating the underlying pathophysiology prior to

    2018-10-30

    Interrogating the underlying pathophysiology prior to the full-blown manifestations can help clarify some confounding effects. For example, extant neuroimaging research on established BP has suggested that the volume of gray matter (GM) decreases in the regions underpinning emotion processing and regulation and cognitive processes, such as the ventrolateral prefrontal cortex (vlPFC), orbitofrontal cortex (OFC) and amygdala (Phillips and Swartz, 2014). Nevertheless, these changes more likely reflect the net effect of inherited neuropathological vulnerability and a number of contributing factors including illness progression, symptoms (e.g., psychotic symptoms), comorbid conditions, and medications such as lithium that can normalize or increase GM volumes (Kalmar et al., 2009; Moore et al., 2000; Moorhead et al., 2007; Nugent et al., 2006; Strasser et al., 2005). Brain network analysis has been increasingly adopted in neuroscience research. This method provides useful information about order eicosapentaenoic acid organization in terms of how spatially segregated brain regions are integrated globally via connecting fiber tracts (i.e., an anatomical network) to form an integrated system (for a comprehensive review, see (Bullmore and Sporns, 2009)). Accumulating evidence suggests that inter-regional integration is crucial for cognitive performance, particularly for effortful psychological tasks, such as working memory (Kitzbichler et al., 2011). Moreover, brain network analysis is particularly helpful for research on those psychiatric disorders that are conceptualized as dysconnectivity syndromes, such as schizophrenia and BP, disorders that may be caused by the failure of integrating spatially distributed brain regions to form a large-scale network (Catani and ffytche, 2005). Among measures of brain network topology, small-world properties are useful for describing anatomical connectivity networks that reflect a high clustering of functionally associated regions with short path length (high efficiency) (Bassett and Bullmore, 2006; Bullmore and Sporns, 2012). These properties were reported to be heritable in twin studies (Smit et al., 2008), related to cognitive performance (Micheloyannis et al., 2009), and significantly altered in schizophrenia (Bassett et al., 2008; Liu et al., 2008) (a disorder sharing many overlapping features with BP, including genetics). In contrast, assortativity, an index that can be used to measure the robustness to assaults (i.e., structurally abnormal regions) of a brain network (Newman, 2002), may potentially assist in capturing the vulnerability of the UHR stage of BP. At the macroscopic level, cognitive deficits have been demonstrated to be an important aspect of full-blown BP that adversely affects the quality of life in people with the disorder (Wingo et al., 2009). A significant research gap is whether cognitive deficits are the consequences of the course of illness and its related factors, such as medications (e.g., valproate) and recurrent subthreshold syndromes (Martinez-Aran et al., 2004; Rosa et al., 2014; Xu et al., 2012), or are inherited, e.g., the deficits in visual–spatial memory (Ferrier et al., 2004) and working memory observed in the “unaffected” relatives of patients with BP (Kulkarni et al., 2010). Indeed, our previous study showed that patients with BP, following clinical remission from depression after six-week treatments, did not recover their processing speed and visual–spatial memory functioning (Xu et al., 2012). To fill the research gap, it is necessary to investigate whether cognitive deficits exist in genetically high-risk individuals at the very early stages before the onset of full-blown syndromes. A multi-dimensional approach can inform complementary and mutually informative connections between different levels of descriptions across stages, thus yielding patterns of abnormalities (Phillips and Kupfer, 2013). Such an approach may assist in understanding how neural substrates affect cognitive function and behavioral phenotypes across stages.