کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
6268732 | 1614645 | 2014 | 13 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
An automated approach towards detecting complex behaviours in deep brain oscillations
ترجمه فارسی عنوان
یک رویکرد خودکار برای شناسایی رفتارهای پیچیده در نوسانات مغزی عمیق
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موضوعات مرتبط
علوم زیستی و بیوفناوری
علم عصب شناسی
علوم اعصاب (عمومی)
چکیده انگلیسی
Extracting event-related potentials (ERPs) from neurological rhythms is of fundamental importance in neuroscience research. Standard ERP techniques typically require the associated ERP waveform to have low variance, be shape and latency invariant and require many repeated trials. Additionally, the non-ERP part of the signal needs to be sampled from an uncorrelated Gaussian process. This limits methods of analysis to quantifying simple behaviours and movements only when multi-trial data-sets are available. We introduce a method for automatically detecting events associated with complex or large-scale behaviours, where the ERP need not conform to the aforementioned requirements. The algorithm is based on the calculation of a detection contour and adaptive threshold. These are combined using logical operations to produce a binary signal indicating the presence (or absence) of an event with the associated detection parameters tuned using a multi-objective genetic algorithm. To validate the proposed methodology, deep brain signals were recorded from implanted electrodes in patients with Parkinson's disease as they participated in a large movement-based behavioural paradigm. The experiment involved bilateral recordings of local field potentials from the sub-thalamic nucleus (STN) and pedunculopontine nucleus (PPN) during an orientation task. After tuning, the algorithm is able to extract events achieving training set sensitivities and specificities of [87.5 ± 6.5, 76.7 ± 12.8, 90.0 ± 4.1] and [92.6 ± 6.3, 86.0 ± 9.0, 29.8 ± 12.3] (mean ± 1 std) for the three subjects, averaged across the four neural sites. Furthermore, the methodology has the potential for utility in real-time applications as only a single-trial ERP is required.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Neuroscience Methods - Volume 224, 15 March 2014, Pages 66-78
Journal: Journal of Neuroscience Methods - Volume 224, 15 March 2014, Pages 66-78
نویسندگان
Michael Mace, Nada Yousif, Mohammad Naushahi, Khondaker Abdullah-Al-Mamun, Shouyan Wang, Dipankar Nandi, Ravi Vaidyanathan,