This week’s Cog Lunch features a talk by Asaf Bachrach.
Title: fMRI investigation of incremental language processing in a naturalistic context
Time: 10/14 at 12pm, 46-3189
Our study examined brain activation in a naturalistic language processing task, with a particular focus on the temporal dynamics inherent to this complex cognitive task. Sentence processing, in particular in the auditory modality, is incremental. The structure and associated compositional meaning of a sentence are not provided to the listener instantaneously, but require integration over multiple temporally spaced inputs. Behavioral and electrophysiological evidence (a small sample of which will be reviewed) point out that the human parser makes use of an `eager’ strategy, incrementally constructing the eventual sentential representation based on partial input. In addition, it appears that this incremental strategy is probabilistic and parallel. The parser considers potentially multiple alternative analyses, which are probabilistically weighted. Most behavioral and imaging paradigms used to explore aspects of incremental auditory sentence processing have been limited by the use of qualitative or binary contrasts and by a sparse sampling approach (often only one data point per sentence). In this talk we will present the results of a novel imaging paradigm that attempts to overcome the above limitations.
We used functional Magnetic Resonance Imaging (fMRI) to monitor brain activation while subjects passively listen to short narratives. The texts were written so as to introduce various syntactic complexities (relative clauses, embedded questions, etc.) not usually found (in such density) in actual corpora. With the use of computationally implemented probabilistic parser (taken to represent an ‘ideal listener’) we have calculated a number of temporally dense (one per word) parametric measures reflecting different aspects of the incremental processing of each sentence. We used the resulting measures to model the observed brain activity (BOLD). We were able to identify different brain networks that support incremental linguistic processing and characterize their particular function.
In the talk we will present data regarding the effect of contextually based prediction (or surprisal), distinguishing lexical and syntactic prediction, and the effect of local structural ambiguity, distinguishing the effects of uncertainty from these of reanalysis.