Syntactic and Semantic Predictors of Tense in Hindi: An ERP Investigation

Brian Dillon, Andrew Nevins, Alison C. Austin, Colin Phillips

Although there is broad agreement that many ERP components reflect error signals generated during an unexpected linguistic event, there are least two distinct aspects of the process that the ERP signals may reflect. The first is the content of an error, which is the local discrepancy between an observed form and any expectations about upcoming forms, without any reference to why those expectations were held. The second aspect is the cause of an error, which is a context-aware analysis of why the error arose. The current study examines the processes involved in prediction of past tense marking on verbal morphology in Hindi. This is a case where an error with the same local characteristics can arise from very different cues, one syntactic in origin (ergative case marking), and the other semantic in origin (a past tense adverbial). Results suggest that the parser does indeed track the cause in addition to the content of errors. Despite the fact that the critical manipulation of verb tense marking was identical across cue types, the nature of the cue led to distinct patterns of ERPs in response to anomalous verbal morphology. When verb tense was predicted based upon semantic cues, an incorrect future tense form elicited an early negativity in the 200-400 ms interval with a posterior distribution. In contrast, when verb tense was predicted based upon morphosyntactic cues, an incorrect future tense form elicited a right-lateralized anterior negativity (RAN) during the 300-500 ms interval, as well as a P600 response with a broad distribution.