本文選題：失匹配負(fù)波 + 擴(kuò)散模型　； 參考：《中國生物醫(yī)學(xué)工程學(xué)報(bào)》2016年01期

【摘要】：失匹配負(fù)波(MMN)是否受注意力的調(diào)控,一直是MMN研究領(lǐng)域的爭論問題。目前鮮有實(shí)驗(yàn)范式能夠很好地控制受試者注意力在注意通路與非注意通路之間的分配,并缺乏一個量化尺度來反映受試者注意力資源分配的變化。擴(kuò)散模型是一種認(rèn)知過程模型,主要通過研究完成任務(wù)過程中的反應(yīng)時間和準(zhǔn)確率等行為數(shù)據(jù)來揭示其潛在的神經(jīng)加工機(jī)理。因此,建立一種新的跨通路延遲反應(yīng)實(shí)驗(yàn)范式,以更好地描述受試者注意力的分配;然后結(jié)合擴(kuò)散模型參數(shù)擬合方法,量化受試者注意力資源分配情況,并明確MMN的潛伏期和峰值與注意力之間的關(guān)系。采集18名受試者在3組不同圖像對比度實(shí)驗(yàn)條件下的腦電信號,研究對比9個導(dǎo)聯(lián)的標(biāo)準(zhǔn)刺激與偏差刺激ERP波形。實(shí)驗(yàn)結(jié)果表明,擴(kuò)散模型擬合參數(shù)可以解釋實(shí)驗(yàn)中不同設(shè)定條件對受試者注意力分配的影響,從而定量地確定受試者的注意力。同時表明,MMN的峰潛伏期隨實(shí)驗(yàn)條件變化顯著,與對應(yīng)的擴(kuò)散模型參數(shù)有顯著的相關(guān)性:MMN峰潛伏期與擴(kuò)散模型擬合參數(shù)邊界間隔、漂移率和非決策時間之間的相關(guān)系數(shù)分別為0.63、0.58和0.63。結(jié)果證實(shí),擴(kuò)散模型參數(shù)可以作為MMN測試中受試者的注意力資源分配的指標(biāo),且MMN的峰潛伏期與受試者注意力呈正相關(guān),因此可以認(rèn)為MMN具有半自動加工的性質(zhì)。
[Abstract]:Whether mismatched negative wave (MMN) is regulated by attention has always been a controversial issue in MMN. At present, there are few experimental paradigms which can control the distribution of attention between attention pathway and non-attention pathway, and lack a quantitative scale to reflect the change of attention resource allocation. Diffusion model is a cognitive process model, which reveals its potential neural processing mechanism by studying the behavior data such as reaction time and accuracy rate in the process of task completion. Therefore, a new experimental paradigm of cross-pathway delayed response is established to better describe the distribution of participants' attention, and then, combining with the parameter fitting method of diffusion model, the allocation of attention resources is quantified. The relationship between latency and peak value of MMN and attention was clarified. The electroencephalogram (EEG) signals were collected from 18 subjects in three groups of different image contrast experiments, and the ERP waveforms of 9 leads were compared with those of standard stimulus and bias stimulus. The experimental results show that the fitting parameters of the diffusion model can explain the effects of different conditions on the distribution of the subjects' attention and thus determine the attention of the subjects quantitatively. At the same time, the peak latency of MMN changed significantly with the experimental conditions, and there was a significant correlation between the peak latency of MMMN and the corresponding parameters of diffusion model. The correlation coefficients between drift rate and non-decision time are 0.63t 0.58 and 0.63, respectively. The results show that the diffusion model parameters can be used as indicators of attention resource allocation in MMN test, and the peak latency of MMN is positively correlated with the participants' attention, so it can be considered that MMN has the property of semi-automatic processing.
【作者單位】： 大連理工大學(xué)電子信息與電氣工程學(xué)部;大連大學(xué)附屬中山醫(yī)院;
【基金】：國家自然科學(xué)基金(61573079) 中央高校基本科研業(yè)務(wù)費(fèi)專項(xiàng)資金 “數(shù)字制造裝備與技術(shù)”國家重點(diǎn)實(shí)驗(yàn)室(華中科技大學(xué))開放課題(DMETKF2015007)
【分類號】：R338;TP274

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