Magazzini Lorenzo, Muthukumaraswamy Suresh D, Campbell Anne E, Hamandi Khalid, Lingford-Hughes Anne, Myers Jim F M, Nutt David J, Sumner Petroc, Wilson Sue J, Singh Krish D
Cardiff University Brain Research Imaging Centre, School of Psychology, Cardiff University, Cardiff, CF24 4HQ, United Kingdom.
School of Pharmacy, Faculty of Medical and Health Sciences, Auckland University, Auckland, 1123, New Zealand.
Hum Brain Mapp. 2016 Nov;37(11):3882-3896. doi: 10.1002/hbm.23283.
The frequency of visual gamma oscillations is determined by both the neuronal excitation-inhibition balance and the time constants of GABAergic processes. The gamma peak frequency has been linked to sensory processing, cognitive function, cortical structure, and may have a genetic contribution. To disentangle the intricate relationship among these factors, accurate and reliable estimates of peak frequency are required. Here, a bootstrapping approach that provides estimates of peak frequency reliability, thereby increasing the robustness of the inferences made on this parameter was developed. The method using both simulated data and real data from two previous pharmacological MEG studies of visual gamma with alcohol and tiagabine was validated. In particular, the study by Muthukumaraswamy et al. [] (Neuropsychopharmacology 38(6):1105-1112), in which GABAergic enhancement by tiagabine had previously demonstrated a null effect on visual gamma oscillations, contrasting with strong evidence from both animal models and very recent human studies was re-evaluated. After improved peak frequency estimation and additional exclusion of unreliably measured data, it was found that the GABA reuptake inhibitor tiagabine did produce, as predicted, a marked decrease in visual gamma oscillation frequency. This result demonstrates the potential impact of objective approaches to data quality control, and provides additional translational evidence for the mechanisms of GABAergic transmission generating gamma oscillations in humans. Hum Brain Mapp 37:3882-3896, 2016. © 2016 Wiley Periodicals, Inc.
视觉伽马振荡的频率由神经元兴奋-抑制平衡和GABA能过程的时间常数共同决定。伽马峰值频率与感觉处理、认知功能、皮质结构有关,并且可能具有遗传因素。为了理清这些因素之间的复杂关系,需要对峰值频率进行准确可靠的估计。在此,我们开发了一种自展方法,该方法可提供峰值频率可靠性的估计,从而增强基于此参数所做推断的稳健性。使用来自之前两项关于酒精和噻加宾对视觉伽马影响的药理学MEG研究的模拟数据和真实数据对该方法进行了验证。特别是,重新评估了Muthukumaraswamy等人[](《神经精神药理学》38(6):1105 - 1112)的研究,在该研究中,噻加宾增强GABA能此前已证明对视觉伽马振荡无影响,这与动物模型和近期人体研究的有力证据形成对比。在改进峰值频率估计并进一步排除测量不可靠的数据后,发现GABA再摄取抑制剂噻加宾确实如预期那样使视觉伽马振荡频率显著降低。该结果证明了客观的数据质量控制方法的潜在影响,并为人类中GABA能传递产生伽马振荡的机制提供了额外的转化证据。《人类大脑图谱》37:3882 - 3896,2016年。© 2016威利期刊公司