60 research outputs found

    Research Achievements in Use and Comprehension of Local Dialect in Japan on Children/Person with Autism Spectrum Disorders.

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    方言主流社会における発達障害に関わる療育・教育関係者の間で語られていた「自閉症は方言を話さない」とする風聞をきっかけにして、ASD の方言使用・理解の研究が進められている。これまで特別支援教育関係者を対象にした質問調査は、ASD の方言不使用という印象が全国で共通するものであること、および方言語彙使用が少ないことを示した。また、ASD の方言理解及びことばの使い分けについての実験的研究の結果は、方言理解自体にも困難を抱えることおよび相手との関係が不明瞭な場合のことばの使い分けに特徴的な反応が見られることを示している。これらの現象の要因として、ASD の社会性の障害に原因を求める説が松本らによって提出されていた。一方、音響音声学の研究者からはASD の音声処理にその原因を求める説が提出されている。本研究ではこれらの研究を概括し、ASD の音声処理、言語習得、そしてことばの使い分けの背景に存在する問題について理論的検討を加えた。There is a rumor among some teachers of special support education at Tsugaru Area in Aomori Prefecture in northern Japan. “Children with Autism do not speak Tsugaru dialect.” A series of studies on the use of local dialects were conducted. The results of the studies indicated the following; 1) the impression with non-use of local dialect in ASD is widespread on the teacher of special support education, 2) the students with ASD in special education schools do not use vocabularies in local dialects. Also, experimental studies report that children with ASD in local dialect society have a difficulty of comprehension of dialect in compared to children with typical development and that children with ASD show characteristic patterns in the change of speaking according to the relationship and scene. As a cause of this phenomenon, Matsumoto et al. (2017) cited social disability relative to the social function of local dialects. On the other hand, a researcher of acoustic phonetics points out the peculiarity of auditory processing in ASD as the cause. Based on these studies, the difficulties in which children with ASD show in use and comprehension in local dialects are discussed

    Correlations of amide proton transfer-weighted MRI of cerebral infarction with clinico-radiological findings.

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    OBJECTIVE:To clarify the relationship between amide proton transfer-weighted (APTW) signal, which reflects intracellular pH, and clinico-radiological findings in patients with hyperacute to subacute cerebral infarction. MATERIALS AND METHODS:Twenty-nine patients (median age, 70 years [IQR, 54 to 74]; 15 men) were retrospectively examined. The 10th, 25th, 50th, 75th, and 90th percentiles of APTW signal (APT10, APT25, APT50, APT75 and APT90, respectively) were measured within the infarction region-of-interest (ROI), and compared between poor prognosis and good prognosis groups (modified Rankin Scale [mRS] score ≥2 and mRS score <2, respectively). Correlations between APTW signal and time after onset, lesion size, National Institutes of Health Stroke Scale (NIHSS) score, mRS score, and mean apparent diffusion coefficient (ADC) were evaluated. RESULTS:The poor prognosis group had lower APT50, APT75, and APT90 than the good prognosis group (-0.66 [-1.19 to -0.27] vs. -0.09 [-0.62 to -0.21]; -0.27 [-0.63 to -0.01] vs. 0.31 [-0.15 to 1.06]; 0.06 [-0.21 to 0.34] vs. 0.93 [0.36 to 1.50] %; p <0.05, respectively). APT50 was positively correlated with time after onset (r = 0.37, p = 0.0471) and negatively with lesion size (r = -0.39, p = 0.0388). APT75 and APT90 were negatively correlated with NIHSS (r = -0.41 and -0.43; p <0.05, respectively). APT50, APT75 and APT90 were negatively correlated with mRS (r = -0.37, -0.52 and -0.57; p <0.05, respectively). APT10 and APT25 were positively correlated with mean ADC (r = 0.37 and 0.38; p <0.05, respectively). CONCLUSION:We demonstrated correlations between APTW signals of infarctions and clinico-radiological findings in patients with hyperacute to subacute infarctions. The poor prognosis group had a lower APTW signal than the good prognosis group. APTW signal was reduced in large infarctions, infarctions with low ADC, and in patients with high NIHSS and mRS scores

    Alexithymia characteristics are associated with salience network activity in healthy participants: an arterial spin labeling study

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    Abstract Background Alexithymia, a personality trait characterized by difficulties in identifying and expressing their emotions despite having a range of emotional experiences, can impact individuals’ stress coping mechanisms. While many studies have investigated brain functions associated with specific tasks in relation to emotion processing, research focusing on resting-state brain functions has been limited. Thus, the aim of this study was to investigate the relationship between alexithymia and brain function by analyzing arterial spin labeling (ASL) data obtained during the resting state. Methods A brain structural and functional imaging study was conducted on 42 healthy adult men and women using ASL and the 20-item Toronto Alexithymia Scale (TAS-20) questionnaire survey. Cerebral blood flow and functional connectivity values were calculated for regions of interest in the default mode network, saliency network, and central executive network from the ASL data. Correlation analysis was performed with TAS20 scores, and partial correlation analysis was conducted to control for anxiety and depression. Results The functional connectivity analysis revealed a negative correlation between the functional connectivity of the right insular cortex and left anterior cingulate cortex and the total score of TAS, as well as difficulty identifying feelings and difficulty describing feeling subscores, indicating that the higher the scores, the weaker the functional connectivity between these regions (T = -3.830, p = 0.0013, R = -0.5180). This correlation remained significant even after controlling for anxiety and depression using partial correlation analysis. Conclusion The present study revealed differences in the activity of the Saliency Network at rest as measured by ASL, which were independent of anxiety and depression, and varied depending on the severity of alexithymia. This functional change may underlie the neural basis of decreased emotional processing observed in alexithymia. These findings may contribute to the elucidation of the neural mechanisms of alexithymia, which can lead to social impairments, and suggest the usefulness of ASL measurement as a biomarker of alexithymia

    Clinical efficacy of simplified intravoxel incoherent motion imaging using three b-values for differentiating high- and low-grade gliomas.

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    In this study, we evaluated the efficacy of intravoxel incoherent motion (IVIM)-derived parameters calculated with three b-values in differentiating high-grade gliomas (HGGs) from low-grade gliomas (LGGs) by comparing those calculated with multiple b-values. Ten patients with LGG (ages 35.1±12.1 yrs; 4 males, 6 females) and 21 patients with HGG (ages 60.6±19.1 yrs; 10 males, 11 females) who underwent subsequent surgical resections were examined with both IVIM imaging and histopathological analysis. The IVIM diffusion-weighted imaging was conducted using a single-shot echo planar sequence with 13 b-factors (0, 10, 20, 30, 50, 80, 100, 200, 300, 400, 600, 800, and 1000 sec/mm2) at 3T. In the conventional IVIM analysis, the perfusion fraction (f) and true diffusion coefficient (D) were calculated by biexponential fitting model with 13 b-values. In the simplified method with the selected three b-values (0, 300, and 1000 sec/mm2), D simply corresponds to the slope of a straight line passing through two logarithmic signal intensities (SIs) at the b-values of 300 and 1000 s/mm2, and f corresponds to the difference between the intercept of this line and SI at the b-value of 0 sec/mm2. The maximum f (f-max) and minimum D (D-min) was measured in each tumor. The f-max values calculated with three b-values (12.8±5.9%) were significantly lower than those with 13 b-values (17.3±7.5%, p<0.0001), but a good correlation and agreement were observed between these sets of f-max values (r = 0.79, ICC = 0.87). In the IVIM imaging with both three and 13 b-values, the HGGs showed significantly higher f-max values compared to the LGGs (p<0.001, respectively). The D-min values calculated with three b-values (1.06±0.31 ×10-3 mm2/sec) was not different from those with 13 b-values (1.07±0.33 ×10-3 mm2/sec), and an excellent correlation and agreement were found between them (r = 0.99, ICC = 0.99). The simplified IVIM imaging using three b-values can efficiently differentiate HGGs and LGGs
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