Neuromagnetic reflections of harmony and constraint violations in Turkish

Predictive coding of phonological rules in auditory cortex: A mismatch negativity study

“…As discussed above, neither is the data pattern explained by acoustic or phonetic processing. Thus, in line with previous studies suggesting that predictions about following speech sounds may be generated on the basis of phonological knowledge (e.g., Hwang et al, 2010;Poeppel & Monahan, 2011;Scharinger et al, 2011Scharinger et al, , 2012Weber, 2011), we can conclude that our findings were driven by phonology. This interpretation is compatible with the observation of maximal amplitudes at central electrodes, since also Steinberg et al's (in press) recent study on the effect of context on phonologically driven MMN focused on central scalp sites.…”

“…Taken together, the present and previous findings suggest that the processing of continuous speech in natural communication is likely facilitated by hierarchically organised levels of predictive coding. These may include syntax (Pulvermüller et al, 2008), word recognition (Gagnepain et al 2012;Ylinen et al, submitted), and phonological processing, as suggested by the present and previous studies (Hwang et al, 2010;Poeppel & Monahan, 2011;Scharinger et al, 2011Scharinger et al, , 2012Weber, 2011). Investigating language learner's brain responses during the learning process could shed light on when and how these neural phonological predictions are formed.…”

“…In the superior temporal gyrus (STG), this resulted both in an increased gradiometer field potential for the novel word and in a decreased field potential for the familiar word (Gagnepain et al, 2012), results not anticipated by prior lexical competition accounts (for these accounts, see Gaskell and Marslen-Wilson, 1997;McClelland and Elman, 1986;Norris and McQueen, 2008). In addition to predictions driven by lexical representations (see also Bendixen, Scharinger, Strauss, & Obleser, 2014), previous studies have suggested that predictions about following speech sounds may be generated on the basis of phonological knowledge (e.g., Hwang, Monahan, & Idsardi, 2010;Poeppel & Monahan, 2011;Scharinger, Idsardi, & Poe, 2011;Scharinger, Bendixen, Trujillo-Barreto, & Obleser, 2012;Weber, 2011).…”

A Sparse Neural Code for Some Speech Sounds but Not for Others

“…We are further aware that it is difficult to derive generalizations from a single contrast, involving two different words only. While this is a technical constraint of MMN studies, necessitating a large number of repetitions in a reasonable amount of time, our results can be taken as converging evidence for less specific representations of coronals, if compared to behavioral and neurophysiological studies that showed the same findings in other sounds, words, or languages [11] , [12] , [13] , [47] , [48] , [49] , [96] , [97] , [98] . We therefore conclude that the predictive coding approach together with the assumption of sparse neural codes provides the best account of our data.…”