At the beginning, I would like to give my special thanks to Professor Woo Jihwan, who provided me a wonderful chance to be a student as well as a researcher in the CNE laboratory, which I earned wonderful experiences and valuable times. Language is one of the factors that can affect people's understanding depending on the skill of the speaker. This may be associated with the difference in brain responses to speech stimuli between native and non-native speakers.
This study provides insight into brain activation pattern discrepancies among speakers (native vs non-native) based on the aforementioned model, but only with respect to semantics and grammar. Our results show the language effect in early and late processing in both native and non-native speakers. The signal at the top presents the speech sentence in experiment with a duration of less than 2 seconds).
INTRODUCTION
- Research basis and objective
- Basic brain anatomy and function
- The language-related circuit
- Role of temporal lobe
- Role of IFG
- The auditory language comprehension model
- Electroencephalography
This inspired future studies investigating the effect of speech perception in non-native speakers using continuous speech stimuli. However, there is a dearth of work investigating the difference in oscillatory dynamics between native and non-native listeners. This study aims to understand the cortical mechanism of language processing between native and non-native speakers by measuring the continuous speech EEG signal and using the correlation function calculated based on the speech features of the stimuli.
In addition to the analysis of pure speech presentation, we want to see the difference between the brain activation of native and non-native speakers according to the degraded stimuli of continuous English speech. Sensory association areas are cortical regions that monitor and interpret information arriving in sensory areas of the cortex. The visual association area monitors activity patterns in the visual cortex and interprets the results.
The neuron in the primary motor cortex must be stimulated by neurons in other parts of the brain. Extend along the edge of the premotor cortex in the same hemisphere as the general area of interpretation. From a different perspective (Friederici, 2002; Hickok & Poeppel, 2007; Vigneau et al., 2006), the language-relevant cortex includes Broca's area in the inferior frontal gyrus (IFG), Wernicke's area in the superior temporal gyrus (STG), as well as parts of the middle temporal gyrus (MTG) and the parietal and inferior angular gyrus in the parietal lobe were involved in language perception (Figure 1).
This review (Bookheimer, 2002; Friederici, 2002; . Grodzinsky, 2000; Grodzinsky & Friederici, 2006) shows evidence that some factor such as syntactic complexity, a combination between syntactic complexity and working memory or a combination between syntactic complexity and task demands , may influence the neural response in the IFG. The N100 which reflects the process of acoustic-phonetic is activated in the early time (0 – 100 ms) at primary audio cortex. In the language component processing step, which occurs in the left hemisphere between 150 ms and 800 ms, there are 3 main periods.
Electroencephalography (EEG), a measured method that records the brain's electrical activity, was first recorded in humans by a German physiologist, Hans Berger, in 1924.
BASIS THEORY
EEG recording system
- Experiment diagram
- Devices and toolboxes
- Experiment procedure
Thirteen native (American) and thirteen non-native (Korean) normal-hearing participants (male: 10, female: 17) were recruited into this study. Specifically, native speakers were recruited at the University of Iowa, USA, and non-native speakers were recruited at the University of Ulsan, Korea. The data of one male, a non-native participant, was omitted due to his long performance.
In the case of non-native speakers, Korean is reported to be the first language and they have a low level of English (L2) proficiency. All subjects sat on a chair at a distance of 1 m from the loudspeaker in a sound-proof room and watched movies without sound during the experiments. All study procedures were reviewed and approved by the two Institutional Review Boards of the University of Iowa and the University of Ulsan.
The Biosemi system then records the signals and stores them on the server for offline processing. In preparation for the experiment, participants were asked to wear the electrode holder cap, which holders. Then electrode holders were filled with electrode gel with a syringe to improve the contact between the electrodes and our scalp; then the electrodes were put on the cap and connected to the Biosemi system.
Then, via a CIS strategy (CIS reference), ten eight-channel vocoded sentences corresponding to ten natural sentences were created. Subjects were exposed to both natural and spoken sentences played randomly by the loudspeaker in the passive listening task (vocalized sentences were played before natural sentences to reduce the learning effect of the natural state).
Data processing procedure
- EEG recording and processing
- EEG analysis
After removing artifacts, epochs that exceeded the range -100 uV to 100 uV were excluded from the data. The ERPs were calculated by averaging the remaining epochs of each sentence after eliminating out-of-bound epochs and subtracting the baseline, which ranged from −200 to 0 ms. The phoneme onset impulse train, which is actually the onset times of phonemes in each sentence, was extracted for natural and vocoded sentences with Webmaus.
Then, the neural response to continuous speech, illustrated as in Figure 1E, was calculated based on a cross-correlation function between the ERP (Figure 10) and the combined functions corresponding to each sentence. The cross-correlation function with a time delay of -200 to 800 ms was obtained by applying the 5th Butterworth high-pass filter with a cutoff frequency of 1 Hz. Finally, the grand average was calculated across all subjects for each case involving native native sentence, native vocoded sentence, non-native natural sentence, and non-native vocoded sentence.
The event-related spectral perturbation (ERSP) of each sentence was obtained by averaging the entire spectrum of the corresponding trials. To observe how the limitation of the oscillatory response to the stimuli, the correlation function between the ERSP and the stimuli was evaluated as described in Fig. In the last step, the overall mean cross-correlation spectrum was calculated across all subjects for each case, as in the CSEP analysis.
RESULTS
The graph also indicates that the non-native case's amplitude tends to be more negative in the period from 250 to 500 ms and more positive after 500 ms compared to that of the native case. 22 To compare the average cross-correlation coefficient in 3 main syntactic and semantic processing steps between native and non-native listeners, the average value of the grand average cross-correlation coefficients for 3 time series ms ms, and 500 - 800 ms.) was calculated for all 64 channels . The mean value in the non-native case is subtracted from that in the native case to achieve a comparison.
12 illustrates anterior negativity in both native and non-native speakers in the first language processing period. From 250 to 500 ms, the power of the non-native case is more negative than that of the native case in both the anterior cortex and the central locus. 24 Figure 14: Difference between non-native's grand average spectrum and native's grand average spectrum (non-native's – native's) at Fz in vocoded sound case and difference topographies in different periods (The time interval is between -500 ms and 2500 ms relative to the onset of the continuous speech stimuli, with a time step of 500 ms.).
Figures 13 and 14 show the difference spectra and alpha band difference topographies between the non-native and native oscillatory responses in the natural and scrambled sound conditions. It can be seen that the natural sound condition presents non-native listeners' ERD in the left frontal, temporal, central, and parietal cortices during the duration of speech. On the other hand, the scrambled sound condition elicits non-native listeners' ERD in central and frontal sites more than in frontal and left temporal sites, although this ERD may not result from speech.
25 Figure 15: The difference between the cross-correlation spectrum of the non-native and the correlation spectrum of the native (non-native - native) in F5 in the cases of natural sound and alpha band power topographies in 4. The difference plots show the ERD- in significant alpha of non-native listeners (p values<0.05) in the left frontal, left temporal, central, parietal and occipital areas (Fig. 15).
DISCUSSION AND CONCLUSION
28 In this study, the delay in P1 and N1 peak between the native and non-native case was evident. Here, ELAN is elicited in the original case, and this early negativity may be a result of how easy it is to categorize word information (function words, morphological information, etc.) from the stimulus sentence (Dikker, Rabagliati, & Pylkkanen, 2009; Neville et al., 1991). Interestingly, the N1 peak for non-native listeners in Fig. 11 delayed to mid-phase compared to the N1 peak for native listeners.
Moreover, (Knosche, Maess, & Friederici, 1999) revealed the activation of anterior negativity (AN) instead of left anterior negativity (LAN) in the processing of syntactic information, suggesting that the right hemisphere is involved in auditory language processing to supports the left hemisphere handles the other tasks. While the former component showed the frontocentral distribution, the latter's distribution spread in the centro-parietal area (Friederici, Hahne, & Saddy, 2002). This conclusion supported our result of the fronto-central site responses across native and non-native cases.
In the natural sound condition, alpha band topographies in the ERSP analysis showed ERD of non-native letters from the beginning of speech to the end of speech. The results of the vocoded audio condition showed no significant differences (p-value<0.05) between non-native and native spectra in the alpha frequency band (Figure 16). By using constant stimuli (eg speech, story, music) we can find out how the brain can perceive and process information in more natural stimuli.
Second, the limitation of the cross-correlation method in analyzing two signals with common trends leads to spurious responses in the spectrum (Figures 15 and 16). In conclusion, this study examines the difference in speech comprehension tasks between non-native and native listeners by applying the cross-correlation function to ERPs and ERSPs.
