Quantum and Component Analysis of P3a and P3b from Auditory Single Trial ERPs Differentiates Borderline Personality Disorder from Schizophrenia

D. Melkonian, A. Korner, R. Meares, Anthony Harris
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Abstract

Traditional approaches to EEG modelling use the methods of classical physics to reconstruct scalp potentials in terms of explicit physical models of cortical neuron ensembles. The principal difficulty with such approaches is that the multiplicity of cellular processes, with an intricate array of deterministic and random influencing factors, prevents the creation of consistent biophysical parameter sets. An original, empirically testable solution has been achieved in our previous studies by a radical departure from the deterministic equations of classical physics to the probabilistic reasoning of quantum mechanics. This crucial step relocates the models of elementary bioelectric sources of EEG signals from the cellular to the molecular level where ions are considered as elementary sources of electricity. The rationale is that, despite dramatic differences in cellular machineries, statistical factors governed by the rules of the central limit theorem produce the EEG waveform as a statistical aggregate of the synchronized activity of multiple microscale sources. Based on these innovations, we introduce a method of comprehensive computerized analysis of event related potentials directly from single trial recordings. This method provides a universal model of single trial ERP components in both frequency and time domains. For the first time, this tool provides effective quantification of all significant cognitive components in single trial ERPs and represents a viable alternative to the traditional method of averaging. We demonstrate the clinical significance of the additional information provided by the new method, using ERP data from patients with borderline personality disorder and schizophrenia. Referring to the P300 as an important objective marker of psychiatric disorders, we show that the new method reliably identifies P3a and P3b as the major components of the P3. The diagnostic significance of differentiating the P3a and P3b components of P3 is that it provides an objective electrophysiological measure that distinguishes borderline personality disorder from schizophrenia.
听觉单试验ERPs中P3a和P3b的量子和成分分析区分边缘型人格障碍和精神分裂症
传统的脑电建模方法使用经典物理方法根据皮层神经元集合的显式物理模型来重建头皮电位。这种方法的主要困难在于,细胞过程的多样性,以及一系列复杂的确定性和随机影响因素,阻碍了建立一致的生物物理参数集。在我们以前的研究中,通过从经典物理的确定性方程到量子力学的概率推理的根本背离,已经获得了一个原始的,经验可检验的解决方案。这一关键步骤将脑电图信号的基本生物电源模型从细胞水平重新定位到离子被认为是基本电源的分子水平。其基本原理是,尽管细胞机制存在巨大差异,但受中心极限定理规则支配的统计因素产生的脑电图波形是多个微尺度源同步活动的统计汇总。基于这些创新,我们介绍了一种直接从单次试验记录中对事件相关电位进行综合计算机分析的方法。该方法在频域和时域上提供了单一试验ERP分量的通用模型。该工具首次提供了对单次试验erp中所有重要认知成分的有效量化,代表了传统平均方法的可行替代方案。我们利用边缘型人格障碍和精神分裂症患者的ERP数据,证明了新方法提供的额外信息的临床意义。参考P300作为精神疾病的重要客观标志物,我们表明新方法可靠地识别P3a和P3b是P3的主要成分。区分P3的P3a和P3b组分的诊断意义在于,它提供了区分边缘型人格障碍和精神分裂症的客观电生理指标。
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