High-frequency oscillations are markers of epileptic tissue. Recently, different patterns of EEG background activity were described from which high-frequency oscillations occur: high-frequency oscillations with continuously oscillating background were found to be primarily physiological, those from quiet background were linked to epileptic tissue. It is unclear, whether these interactions remain stable over several days and during different sleep-wake stages. High-frequency oscillation patterns (oscillatory vs. quiet background) were analysed in 23 patients implanted with depth and subdural grid electrodes. Pattern scoring was performed on every channel in 10 s intervals in three separate day- and night-time EEG segments. An entropy value, measuring variability of patterns per channel, was calculated. A low entropy value indicated a stable occurrence of the same pattern in one channel, whereas a high value indicated pattern instability. Differences in pattern distribution and entropy were analysed for 143 280 10 s intervals with allocated patterns from inside and outside the seizure onset zone, different electrode types and brain regions. We found a strong association between high-frequency oscillations out of quiet background activity, and channels of the seizure onset zone (35.2% inside versus 9.7% outside the seizure onset zone, P < 0.001), no association was found for high-frequency oscillations from continuous oscillatory background (P = 0.563). The type of background activity remained stable over the same brain region over several days and was independent of sleep stage and recording technique. Stability of background activity was significantly higher in channels of the seizure onset zone (entropy mean value 0.56 ± 0.39 versus 0.64 ± 0.41; P < 0.001). This was especially true for the presumed epileptic high-frequency oscillations out of quiet background (0.57 ± 0.39 inside versus 0.72 ± 0.37 outside the seizure onset zone; P < 0.001). In contrast, presumed physiological high-frequency oscillations from continuous oscillatory backgrounds were significantly more stable outside the seizure onset zone (0.72 ± 0.45 versus 0.48 ± 0.53; P < 0.001). The overall low entropy values suggest that interactions between high-frequency oscillations and background activity are a stable phenomenon specific to the function of brain regions. High-frequency oscillations occurring from a quiet background are strongly linked to the seizure onset zone whereas high-frequency oscillations from an oscillatory background are not. Pattern stability suggests distinct underlying mechanisms. Analysing short time segments of high-frequency oscillations and background activity could help distinguishing epileptic from physiologically active brain regions.
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机译：高频振荡是癫痫组织的标志物。最近，描述了从中发生了不同模式的EEG背景活动，从中发生了高频振荡：与连续振荡背景的高频振荡被发现主要是生理的，安静背景中的那些与癫痫组织有关。目前尚不清楚，这些相互作用在几天内仍然稳定，在不同的睡眠追逐期间。分析了植入深度和软栅电极的23例患者分析了高频振荡模式（振荡与安静背景）。在三个单独的日期和夜间脑电图段中，在10个间隔的每个频道上进行模式评分。计算熵值，测量每个通道的模式的可变性。低熵值指示一个通道中的相同模式的稳定发生，而高值指示的图案不稳定性。分析了图案分布和熵的差异，分析了来自癫痫发作区域的内外和外部的分配模式，不同的电极类型和脑区域。我们发现高频振荡与安静的背景活动之间的强大关联，并且癫痫发作区域的通道（癫痫发作区域外的35.2％与9.7％，P <0.001），没有找到高频振荡的关联来自连续振荡背景（P = 0.563）。在几天内，背景活动的类型仍然稳定，并且与睡眠阶段和记录技术无关。癫痫发作区域的通道中背景活性的稳定性显着高（熵平均值0.56±0.39与0.64±0.41; p <0.001）。这对于假定的癫痫高频振荡尤其如此（内部0.57±0.39与癫痫发作区域外的0.72±0.37; P <0.001）。相反，来自连续振荡背景的假定生理高频振荡在癫痫发作区域外显着稳定（0.72±0.45与0.48±0.53; p <0.001）。整体低熵值表明，高频振荡和背景活动之间的相互作用是特异于脑区功能的稳定现象。从安静的背景发生的高频振荡与癫痫发作区域强烈连接，而来自振荡背景的高频振荡不是。模式稳定表明明显的潜在机制。分析高频振荡和背景活动的短时间段可以帮助区分生理活性脑区的癫痫症。
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