کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
6028792 1188705 2014 10 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Fast optical signals in the sensorimotor cortex: General Linear Convolution Model applied to multiple source-detector distance-based data
ترجمه فارسی عنوان
سیگنال های نوری سریع در هسته سنسور حرکتی: مدل کوانتومی خطی عمومی برای داده های مبتنی بر فاصله از چند منبع
کلمات کلیدی
سیگنال نوری سریع قشر سوپراسنسوری، مدل خطی عمومی
موضوعات مرتبط
علوم زیستی و بیوفناوری علم عصب شناسی علوم اعصاب شناختی
چکیده انگلیسی
In this study, we applied the General Linear Convolution Model to detect fast optical signals (FOS) in the somatosensory cortex, and to study their dependence on the source-detector separation distance (2.0 to 3.5 cm) and irradiated light wavelength (690 and 830 nm). We modeled the impulse response function as a rectangular function that lasted 30 ms, with variable time delay with respect to the stimulus onset. The model was tested in a cohort of 20 healthy volunteers who underwent supra-motor threshold electrical stimulation of the median nerve. The impulse response function quantified the time delay for the maximal response at 70 ms to 110 ms after stimulus onset, in agreement with classical somatosensory-evoked potentials in the literature, previous optical imaging studies based on a grand-average approach, and grand-average based processing. Phase signals at longer wavelength were used to identify FOS for all the source-detector separation distances, but the shortest one. Intensity signals only detected FOS at the greatest distance; i.e., for the largest channel depth. There was no activation for the shorter wavelength light. Correlational analysis between the phase and intensity of FOS further confirmed diffusive rather than optical absorption changes associated with neuronal activity in the activated cortical volume. Our study demonstrates the reliability of our method based on the General Linear Convolution Model for the detection of fast cortical activation through FOS.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: NeuroImage - Volume 85, Part 1, 15 January 2014, Pages 245-254
نویسندگان
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