کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
4335909 1295188 2009 11 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Denoising neural data with state-space smoothing: Method and application
موضوعات مرتبط
علوم زیستی و بیوفناوری علم عصب شناسی علوم اعصاب (عمومی)
پیش نمایش صفحه اول مقاله
Denoising neural data with state-space smoothing: Method and application
چکیده انگلیسی

Neural data are inevitably contaminated by noise. When such noisy data are subjected to statistical analysis, misleading conclusions can be reached. Here we attempt to address this problem by applying a state-space smoothing method, based on the combined use of the Kalman filter theory and the Expectation–Maximization algorithm, to denoise two datasets of local field potentials recorded from monkeys performing a visuomotor task. For the first dataset, it was found that the analysis of the high gamma band (60–90 Hz) neural activity in the prefrontal cortex is highly susceptible to the effect of noise, and denoising leads to markedly improved results that were physiologically interpretable. For the second dataset, Granger causality between primary motor and primary somatosensory cortices was not consistent across two monkeys and the effect of noise was suspected. After denoising, the discrepancy between the two subjects was significantly reduced.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Neuroscience Methods - Volume 179, Issue 1, 30 April 2009, Pages 131–141
نویسندگان
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