Poster E60, Thursday, August 22, 2019, 3:45 – 5:30 pm, Restaurant Hall
Imaging Language Functions Using Functional Near-Infrared Spectroscopy: A Combined Correction Method to Improve Signal Quality
Gongting Wang1, Miaomiao Zhu1, Xiaoqian Zhou1, Qing Cai1, Lily Tao1;1East China Normal University
Functional near-infrared spectroscopy (fNIRS) is a non-invasive optical neuroimaging method that is increasingly popular for studying human brain functions. Similar to functional magnetic resonance imaging (fMRI), the method involves calculating task-related neural activations based on hemodynamic changes. Compared to fMRI, fNIRS is cheaper, quieter, more portable, has higher temporal resolution, and is less prone to artifacts arising from head motion. There are also disadvantages, however, particularly lower spatial resolution and lower signal-to-noise ratio compared to fMRI, resulting in variable quality of the fNIRS method. In order for future studies to best utilize the advantages of fNIRS (e.g., portability, greater tolerance of head motion), it is important to find effective signal correction methods, to improve signal quality to a level comparable to more reliable imaging techniques (e.g., fMRI). The present study, therefore, quantitatively compared fNIRS and fMRI methods for studying neural language functions, employing different fNIRS signal correction methods. Participants performed a word generation task, first in an fMRI scanner, then in an fNIRS device one day later. The task involved covertly (i.e., without overt articulations) producing as many words as possible that begin with the displayed letter within the fixed time frame. For baseline, participants saw a nonmeaningful symbol (“^”), and covertly repeated a non-meaningful sound (“bou”). Each trial comprised two events, first a fixation cross (“+”) for 15 s, during which participants were instructed to rest, followed by a cue stimulus for 15s, during which participants performed the experimental or baseline tasks. There were 20 trials in total (10 experimental, 10 baseline), and the whole task lasted 10 min. Blocks alternated between experimental and baseline conditions. Within the experimental condition, letters were presented in a random order for each participant. SPM8 was used to analyze the imaging data. For improving fNIRS signal quality, “correction based on signal improvement” (CBSI) and “temporal derivative distribution repair” (TDDR) methods were used. Correlation coefficient was then calculated between fMRI and corrected fNIRS results from the same participants. Lateralization indices (LI) was also calculated, separately for fMRI and fNIRS data. In the fMRI task, significant activation was seen in left inferior frontal gyrus (BA 44, 45), left superior temporal gyrus (BA 22, 42). Compared to uncorrected fNIRS signal, applying signal correction resulted in stronger activation in left inferior frontal gyrus (BA 44, 45). There was significant correlation between fMRI and fNIRS signal (p < .05), while the LIs obtained from the two methods did not differ significantly (p > .05). In conclusion, by using combined signal correction methods, fNIRS signal can be more reliable, and produces results comparable to that of fMRI when investigating the neural basis of language functions. Further work with different types of language tasks, and different populations are needed confirm the present findings. If shown to be consistently reliable and comparable to fMRI, researchers can then capitalize on the advantages of fNIRS, addressing research questions that may not be easily investigated using fMRI, such as language development in infants and children, interactive communication, and more naturalistic language processing settings.
Themes: Methods, Language Production
Method: Functional Imaging