Deviant neural processing of phonotactic probabilities in adults with dyslexia

Abstract

During language acquisition in the first year of life, children become sensitive to phonotactic probabilities such as the likelihood of speech sound occurrences in the ambient language. Because this sensitivity is acquired at an early age, the extent to which the neural system that underlies speech processing in adults is tuned to these phonological regularities can reflect difficulties in processing language-specific phonological regularities that can persist into adulthood. Here, we examined the neural processing of phonotactic probabilities in 18 adults with dyslexia and 18 non-dyslexic controls using mismatch negativity, a pre-attentive neurophysiological response. Stimuli that differed in phonotactic probability elicited similar mismatch negativity responses among the adults with dyslexia, whereas the controls responded more strongly to stimuli with a high phonotactic probability than to stimuli with a low phonotactic probability, suggesting that controls - but not adults with dyslexia - are sensitive to the phonological regularities of the ambient language. These findings suggest that the underlying neural system in adults with dyslexia is not properly tuned to language-specific phonological regularities, which may partially account for the phonological deficits that are often reported in dyslexic individuals.

ERP mismatch response to phonological and temporal regularities in speech

“…high phonotactic probability and first syllable stress) are processed more efficiently, this should lead to easier change detection, indexed by greater MMN peak amplitudes and/or shorter latencies. This has been shown for phonotactic probability [36][37][38] . However previous studies investigating MMN sensitivity to syllable stress have been primarily conducted in languages with fixed-stress patterns [39][40][41][42] .…”

“…Oddball experiments in adults and children have demonstrated that the MMN component can be modulated by variations in phonotactic probability, i.e. the probability of the co-occurrence of phonemes in a language, where deviants with higher probability have been shown to elicit larger mismatch responses compared to deviants with low probability [36][37][38] . The paradigm has also been applied to study processing of syllable stress patterns in both real and pseudowords [39][40][41][42] .…”

Contributions of Letter-Speech Sound Learning and Visual Print Tuning to Reading Improvement: Evidence from Brain Potential and Dyslexia Training Studies

“…Finally, studies used an MMN paradigm (see Section 2 ) in which the phonotactic probabilities of stimuli are manipulated; that is, the sounds presented differed in their likelihood of occurrence in spoken language [ 130 , 131 ]. The MMN responses in this paradigm are expected to be stronger for stimuli with higher phonotactic probability [ 132 ].…”

“…The MMN responses in this paradigm are expected to be stronger for stimuli with higher phonotactic probability [ 132 ]. Dyslexics showed less sensitivity than typical readers to such enhancement of MMN responses, which was interpreted to reflect a subtle deficit in auditory cortical tuning for phonemic regularities in natural speech [ 130 , 131 ]. Interestingly, some studies in typical readers suggested that lexical knowledge [ 133 ] and orthographic information [ 134 ] could influence perceptual learning of speech, referred to as phonetic recalibration.…”

Using network science in the language sciences and clinic

“…Phonotactic probability has also been implicated in memory for nonwords (Gathercole, Frankish, Pickering & Peaker, 1999; Messer, Leseman, Boom & Mayo, 2010), and in literacy-related skills , as in children learning to spell (Apel, Wolter & Masterson, 2006) and as evidenced by differences in processing stimuli that vary in phonotactic probability in children and adults with dyslexia (Bonte, Poelmans, & Blomert, 2007; Noordenbos et al, 2013). Finally, both electro- and magneto-physiological components have been identified for the processing of stimuli that vary in phonotactic probability (Hunter, 2013; Pylkkänen, Stringfellow, & Marantz, 2002).…”