Event-related responses reflect chunk boundaries in natural speech.

Chunking language has been proposed to be vital for comprehension enabling the extraction of meaning from a continuous stream of speech. However, neurocognitive mechanisms of chunking are poorly understood. The present study investigated neural correlates of chunk boundaries intuitively identified by listeners in natural speech drawn from linguistic corpora using magneto- and electroencephalography (MEEG). In a behavioral experiment, subjects marked chunk boundaries in the excerpts intuitively, which revealed highly consistent chunk boundary markings across the subjects. We next recorded brain activity to investigate whether chunk boundaries with high and medium agreement rates elicit distinct evoked responses compared to non-boundaries. Pauses placed at chunk boundaries elicited a closure positive shift with the sources over bilateral auditory cortices. In contrast, pauses placed within a chunk were perceived as interruptions and elicited a biphasic emitted potential with sources located in the bilateral primary and non-primary auditory areas with right-hemispheric dominance, and in the right inferior frontal cortex. Furthermore, pauses placed at stronger boundaries elicited earlier and more prominent activation over the left hemisphere suggesting that brain responses to chunk boundaries of natural speech can be modulated by the relative strength of different linguistic cues, such as syntactic structure and prosody.

Letter processing in Russian: Does orthography matter?

Prior research has suggested that the identification and encoding of letter positions within letter strings might be influenced by orthography. Letters in transparent languages (e.g., Greek) with regular grapheme-to-phoneme correspondences are processed sequentially, whereas letters in deep languages (e.g., English) are processed in parallel. In three experiments, we used a visual search paradigm to test this hypothesis on Russian-a relatively transparent language. In Experiment 1, we measured the identification speed of Cyrillic letters at each position in the five-element real words or pronounceable pseudowords. In Experiment 2, the performance was compared to random letter strings, and in Experiment 3, to non-linguistic symbol strings. Our results reveal a search pattern similar to English, excluding strictly serial letter computation, which is inconsistent with the orthography hypothesis. Moreover, we showed that the lexical status and the nature of the string (linguistic/non-linguistic) affect response times for Russian and therefore must be accounted for in models of visual word recognition.