The neural basis of psychosis is yet to be fully elucidated, and the brain processing of language in bilinguals is not completely understood [40]. Nevertheless, some authors propose that overlapping brain regions may be involved in L1 processing and psychotic symptoms, whereas L2 language production may involve greater prefrontal activity and a more widespread neural network beyond the language areas in the temporal lobe [36], depending on other factors such as fluency and age of second language acquisition, which have been described to influence language preservation in bilinguals with other conditions such as aphasia [41]. According to Brown and Weisman de Mamani [36], L1 production may activate psychogenic regions in the left temporal lobe, repeatedly associated to positive symptoms of schizophrenia, whereas symptoms could present as less severe in an acquired language if a more diffuse network is involved. This proposal may help to explain our findings. However, the independence between L1 and L2 neural circuitries is far from being established. Studies on aphasia have shown that two languages may share underlying neural circuitries for some linguistic processes, such as phonology, grammar, or semantics, but not for others [7]. The degree of neural overlap between both languages seems to depend on the degree of proficiency in L2 and on the age of acquisition [41,42,43]. In simultaneous bilinguals, that is, those who acquired both languages at the same time and early in life, and in high proficient bilinguals, brain activation is similar in the processing of both languages, mainly in the frontotemporal, temporoparietal, and occipital regions [43,44]. However, in low/moderate proficient bilinguals, mostly sequential bilinguals who acquired the second language later in life, L2 processing involves smaller and more widely distributed areas than L1, with a greater involvement of the right hemisphere [44]. This is consistent with the view that low proficient bilinguals recruit additional areas to compensate for the reduced proficiency, especially right frontal areas, which points out to a more effortful processing in L2 [45].
An obstacle to the validation of polyglot software is the lack of tools that analyze source code written in different programming languages, under a unified framework. Returning to Fig. 3, we have a system formed by two programs, written in different programming languages. Any tool that analyzes this system as a whole must be able to parse these two distinct syntaxes and infer the connection points between them. Work has been performed towards this end, but solutions are still very preliminary. As an example, Maas et al. [33] have implemented automatic ways to check if C arrays are correctly read by Python programs. As another example, Furr and Foster [36] have described techniques to ensure type-safety of OCaml-to-C and Java-to-C bindings.
Influent - Polyglot Pack [All Languages] Activation Code [FULL]l
2ff7e9595c
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