Speech motor learning is important for learning to speak during childhood and maintaining the speech system throughout adulthood. Motor and auditory cortical regions play crucial roles in speech motor learning. This experiment aimed to use transcranial alternating current stimulation, a neurostimulation technique, to influence auditory and motor cortical activity. In this study, we used an auditory-motor adaptation task as an experimental model of speech motor learning. Subjects repeated words while receiving formant shifts, which made the subjects’ speech sound different from their production. During the adaptation task, subjects received Beta (20 Hz), Alpha (10 Hz), or Sham stimulation. We applied the stimulation to the ventral motor cortex that is involved in planning speech movements. We found that the stimulation did not influence the magnitude of adaptation. We suggest that some limitations of the study may have contributed to the negative results.
The purpose of this longitudinal study was to predict /r/ acquisition using acoustic signal processing. 19 children, aged 5-7 with inaccurate /r/, were followed until they turned 8 or acquired /r/, whichever came first. Acoustic and descriptive data from 14 participants were analyzed. The remaining 5 children continued to be followed. The study analyzed differences in spectral energy at the baseline acoustic signals of participants who eventually acquired /r/ compared to that of those who did not acquire /r/. Results indicated significant differences between groups in the baseline signals for vocalic and postvocalic /r/, suggesting that the acquisition of certain allophones may be predictable. Participants’ articulatory changes made during the progression of acquisition were also analyzed spectrally. A retrospective analysis described the pattern in which /r/ allophones were acquired, proposing that vocalic /r/ and the postvocalic variant of consonantal /r/ may be acquired prior to prevocalic /r/, and /r/ followed by low vowels may be acquired before /r/ followed by high vowels, although individual variations exist.
The distinctions between the neural resources supporting speech and music comprehension have long been studied using contexts like aphasia and amusia, and neuroimaging in control subjects. While many models have emerged to describe the different networks uniquely recruited in response to speech and music stimuli, there are still many questions, especially regarding left-hemispheric strokes that disrupt typical speech-processing brain networks, and how musical training might affect the brain networks recruited for speech after a stroke. Thus, our study aims to explore some questions related to the above topics. We collected task-based functional MRI data from 12 subjects who previously experienced a left-hemispheric stroke. Subjects listened to blocks of spoken sentences and novel piano melodies during scanning to examine the differences in brain activations in response to speech and music. We hypothesized that speech stimuli would activate right frontal regions, and music stimuli would activate the right superior temporal regions more than speech (both findings not seen in previous studies of control subjects), as a result of functional changes in the brain, following the left-hemispheric stroke and particularly the loss of functionality in the left temporal lobe. We also hypothesized that the music stimuli would cause a stronger activation in right temporal cortex for participants who have had musical training than those who have not. Our results indicate that speech stimuli compared to rest activated the anterior superior temporal gyrus bilaterally and activated the right inferior frontal lobe. Music stimuli compared to rest did not activate the brain bilaterally, but rather only activated the right middle temporal gyrus. When the group analysis was performed with music experience as a covariate, we found that musical training did not affect activations to music stimuli specifically, but there was greater right hemisphere activation in several regions in response to speech stimuli as a function of more years of musical training. The results of the study agree with our hypotheses regarding the functional changes in the brain, but they conflict with our hypothesis about musical expertise. Overall, the study has generated interesting starting points for further explorations of how musical neural resources may be recruited for speech processing after damage to typical language networks.
The brain continuously monitors speech output to detect potential errors between its sensory prediction and its sensory production (Daliri et al., 2020). When the brain encounters an error, it generates a corrective motor response, usually in the opposite direction, to reduce the effect of the error. Previous studies have shown that the type of auditory error received may impact a participant’s corrective response. In this study, we examined whether participants respond differently to categorical or non-categorical errors. We applied two types of perturbation in real-time by shifting the first formant (F1) and second formant (F2) at three different magnitudes. The vowel /ɛ/ was shifted toward the vowel /æ/ in the categorical perturbation condition. In the non-categorical perturbation condition, the vowel /ɛ/ was shifted to a sound outside of the vowel quadrilateral (increasing both F1 and F2). Our results showed that participants responded to the categorical perturbation while they did not respond to the non-categorical perturbation. Additionally, we found that in the categorical perturbation condition, as the magnitude of the perturbation increased, the magnitude of the response increased. Overall, our results suggest that the brain may respond differently to categorical and non-categorical errors, and the brain is highly attuned to errors in speech.
Methods: Two adults with dyslexia and 4 control adults participated in an auditory gating test using tone pairs. Latencies and Amplitudes for the N100 and P200 responses were recorded and analyzed. Participants were also administered the Abbreviated Torrance Test for Adults (ATTA), a test of creative ability designed to evaluate divergent thinking in individuals. Results were averaged and compared.
Results: The averaged difference in measured N100 amplitudes between tone 1 and tone 2 was significantly larger in the control group compared to the difference observed in the dyslexia group. In particular, one participant with dyslexia who had low scores on a task of rapid word recognition also showed no evidence of gating at the N100 component, whereas the other participant with dyslexia with good word recognition scores showed evidence of intact gating. The averaged difference in measured P200 amplitude between tone 1 and tone 2 was larger in the dyslexia group compared to the control group; however, the difference was small enough to be considered insignificant. The total average ATTA score for the control group was higher than the average of the dyslexia group. This difference in total average was less than one point on a 106-point scale.
Conclusions: Neural sensory gating occurs approximately 100 ms after the onset of a stimulus and is diminished in adults with dyslexia who also have deficits in rapid word recognition. There is a difference in creativity, in terms of divergent thinking, between those with dyslexia and those without (controls scored higher on average); however, the difference is not significant (less than one point). Dyslexia scores were more consistent than controls.
performance is limited by poor spectral resolution. Acoustic CI simulation has been widely used
in normal-hearing (NH) listeners to study the effect of spectral resolution on speech perception,
while avoiding patient-related confounds. It is unclear how speech production may change with
the degree of spectral degradation of auditory feedback as experience by CI users. In this study,
a real-time sinewave CI simulation was developed to provide NH subjects with auditory
feedback of different spectral resolution (1, 2, 4, and 8 channels). NH subjects were asked to
produce and identify vowels, as well as recognize sentences while listening to the real-time CI
simulation. The results showed that sentence recognition scores with the real-time CI simulation
improved with more channels, similar to those with the traditional off-line CI simulation.
Perception of a vowel continuum “HEAD”- “HAD” was near chance with 1, 2, and 4 channels,
and greatly improved with 8 channels and full spectrum. The spectral resolution of auditory
feedback did not significantly affect any acoustic feature of vowel production (e.g., vowel space
area, mean amplitude, mean and variability of fundamental and formant frequencies). There
was no correlation between vowel production and perception. The lack of effect of auditory
feedback spectral resolution on vowel production was likely due to the limited exposure of NH
subjects to CI simulation and the limited frequency ranges covered by the sinewave carriers of
CI simulation. Future studies should investigate the effects of various CI processing parameters
on speech production using a noise-band CI simulation.
on-acquisition of the difficult /r/ phoneme.
stimuli played prior to the onset of speech production. In this experiment, we are examining the
specificity of the auditory stimulus by implementing congruent and incongruent speech sounds in
addition to non-speech sound. Electroencephalography (EEG) data was recorded for eleven adult
subjects in both speaking (speech planning) and silent reading (no speech planning) conditions.
Data analysis was accomplished manually as well as via generation of a MATLAB code to
combine data sets and calculate auditory modulation (suppression). Results of the P200
modulation showed that modulation was larger for incongruent stimuli than congruent stimuli.
However, this was not the case for the N100 modulation. The data for pure tone could not be
analyzed because the intensity of this stimulus was substantially lower than that of the speech
stimuli. Overall, the results indicated that the P200 component plays a significant role in
processing stimuli and determining the relevance of stimuli; this result is consistent with role of
P200 component in high-level analysis of speech and perceptual processing. This experiment is
ongoing, and we hope to obtain data from more subjects to support the current findings.