Language-specific cortical activation patterns for phoneme verbal fluency task in Chinese assessed by functional near-infrared spectroscopy

Journal of Psychological Science ›› 2016, Vol. 39 ›› Issue (3) : 520-526.

PDF(1301 KB)
PDF(1301 KB)
Journal of Psychological Science ›› 2016, Vol. 39 ›› Issue (3) : 520-526.

Language-specific cortical activation patterns for phoneme verbal fluency task in Chinese assessed by functional near-infrared spectroscopy

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Abstract

Verbal fluency task is a kind of traditional psychological test that used to assess individual language fluency ability for transmission of information and a classic paradigm for studying human cognitive and language skills. Since the indicator of this task can distinguish healthy people and patients with certain diseases, it has been widely adopted in some clinical areas, including psychiatry, neurology, neurosurgery and so forth. Because Chinese is a typical Logogram, the neural correlates on the task of its Chinese version may be language-specific. Therefore, the current study investigated brain mechanism when 34 right-handed healthy college students did the Chinese phoneme verbal fluency task assessed by Functional Near Infrared Spectroscopy (fNIRS). 34 right-handed (16 males, 18 females) graduate students participated in the experiment and the measuring instrument for brain was LABNIRS Functional Near Infrared Spectroscopy which was made by Shimadzu company. Experiment design was within-subject design. Participants were asked to sit in a quiet undisturbed lab to complete Chinese phoneme fluency task, meanwhile assessed by LABNIRS in their frontotemporal area, with the indicator of oxygenated hemoglobin concentration (HbO). The total experimental task consisted of 5 blocks and each block continued for 60s, during which the former 30s for the target condition, namely verbal fluency task and the latter 30s for the rest condition. Before the five blocks, practices were necessary in order to prevent confounding variable. The instructor was presented on a computer in front of participants by E-prime software before being tested and experimental materials were Chinese shengmu: /y/,/sh/,/j/,/d/,/x/, which were randomly presented to the subjects. The data were divided into two kinds: behavior and fNIRS data, which were analyzed respectively. The results showed that the subjects in the verbal fluency task generates an average of 7.23 words per 30s, similar to that of previous study and accord with the expectation. The results of fNIRS found that the task significantly activated the pre-central gyrus, post-central gyrus, inferior frontal gyrus, middle frontal gyrus, middle temporal gyrus, supramarginal gyrus on the left hemisphere and right pre-central gyrus, post-central gyrus, inferior frontal gyrus, superior temporal gyrus, supramarginal gyrus which is bilateral activation pattern. When students doing Chinese verbal fluency task, the activation of the brain areas lay in bilateral frontotemporal region. Moreover the language-specific activation areas were found, which may be bilateral supramarginal gyrus, as the featured regions of Chinese phoneme fluency task. In order to get the valuable information further, this study also analyzed the time-course characteristics during task. According to the results, there was a small but obvious fluctuation around 6 seconds and this feature may be a good revelation for healthy subjects in Chinese phoneme fluency task. This study not only can be provided for the clinical application of brain science and but also be regarded as reference data for psychology tests, which can be better for differentiate research between patients with normal in Chinese verbal fluency task. In addition, this discovery is also proof for specific aspects of Chinese language as a typical Logogram.

Key words

phoneme fluency task, Functional Near Infrared Spectroscopy (fNIRS), bilateral supramarginal gyrus, time-course analysis

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Language-specific cortical activation patterns for phoneme verbal fluency task in Chinese assessed by functional near-infrared spectroscopy[J]. Journal of Psychological Science. 2016, 39(3): 520-526
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