Cortico-striatal language pathways dynamically adjust for syntactic complexity: A computational study

• Published in: Brain and language 2017-01, Vol.164, p.53-62
• Main Authors: Szalisznyó, Krisztina, Silverstein, David, Teichmann, Marc, Duffau, Hugues, Smits, Anja
• Format: Article
• Language: English
• Subjects: Comprehension; Comprehension - physiology; Corpus Striatum - physiology; Cortico-striatal language network; Female; Frontal Lobe - physiology; Humans; Language; Language processing; Life Sciences; Linguistics; Male; Memory, Short-Term; Neural Pathways; Neurons and Cognition; Neurosciences; Neurovetenskaper; Phonological memory; Phonological rules; Psychology and behavior; Reservoir computing; Semantics; Sentence comprehension; Short term memory; Simulation; Spoken language; Striatum; Syntactic complexity; Syntactic processing; Thematic roles
• ISSN: 0093-934X; 1090-2155; 1090-2155
• DOI: 10.1016/j.bandl.2016.08.005

•Dynamic recruitment of cortico-striatal pathways are proposed for canonical and non-canonical sentence comprehension.•Modeling results suggest that cortico-striatal circuits dynamically adjusts to syntactic complexity.•Clinical results confirm a critical role for the cortico-striatal network in syntax. A growing body of literature supports a key role of fronto-striatal circuits in language perception. It is now known that the striatum plays a role in engaging attentional resources and linguistic rule computation while also serving phonological short-term memory capabilities. The ventral semantic and the dorsal phonological stream dichotomy assumed for spoken language processing also seems to play a role in cortico-striatal perception. Based on recent studies that correlate deep Broca-striatal pathways with complex syntax performance, we used a previously developed computational model of frontal-striatal syntax circuits and hypothesized that different parallel language pathways may contribute to canonical and non-canonical sentence comprehension separately. We modified and further analyzed a thematic role assignment task and corresponding reservoir computing model of language circuits, as previously developed by Dominey and coworkers. We examined the models performance under various parameter regimes, by influencing how fast the presented language input decays and altering the temporal dynamics of activated word representations. This enabled us to quantify canonical and non-canonical sentence comprehension abilities. The modeling results suggest that separate cortico-cortical and cortico-striatal circuits may be recruited differently for processing syntactically more difficult and less complicated sentences. Alternatively, a single circuit would need to dynamically and adaptively adjust to syntactic complexity.