Different origins of gamma rhythm and high-gamma activity in macaque visual cortex.
Different origins of gamma rhythm and high-gamma activity in macaque visual cortex.
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DOI：
10.1371/journal.pbio.1000610
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发表时间：
2011-04
期刊：
影响因子：
9.8
通讯作者：
Maunsell JH
中科院分区：
文献类型：
--
作者：
Ray S;Maunsell JH
高伽马（80-200 Hz）活动可以从猴子皮层的伽马节律中分离出来，并且似乎主要反映了电极附近的尖峰活动。在认知任务期间，大脑中的电活动在特定频率范围内显示功率的变化，例如α（8-12 Hz）或γ（30-80 Hz）频带，以及在超过1080 Hz的宽范围内，称为高γ频带。这种宽带高伽马活动的作用或意义尚不清楚。一种假设认为，高伽马振荡就像伽马振荡一样，以更高的频率运行，因此时间尺度更快。另一个假设指出，高伽马功率与尖峰活动有关。由于伽马功率和尖峰活动往往在大多数刺激操作（如对比度调制）或认知任务（如注意力调制）过程中共同变化，因此很难将这两个假设分开。我们研究了高伽马功率，伽马节律，尖峰活动在清醒的猴子的初级视觉皮层（V1），而不同的刺激大小，增加了伽马功率，但降低了发射率，允许分离之间的关系。我们发现，伽马功率成为反相关的高伽马功率，这表明这两种现象是不同的，有不同的起源。另一方面，高伽马功率仍然紧密相关的尖峰活动下的广泛的刺激操纵。我们使用称为匹配追踪的信号处理技术研究了这种关系，发现动作电位与宽带功率的LFP中的急剧瞬变相关，这在低至1.50 Hz的频率下可见。这些结果区分宽带高伽马活动的伽马节律作为一个容易获得的和可靠的电生理指标的神经元放电附近的微电极。此外，他们强调了在伽马节律和尖峰相关瞬变之间进行仔细分离的重要性，这些瞬变可能会被错误地分解为使用传统信号处理方法的节律。大脑中的电活动通常显示出不同频率的振荡，例如阿尔法（8-12 Hz）或伽马（30-80 Hz）波段，这些波段与不同的认知状态有关。此外，功率的变化出现在1080 Hz以上的宽范围内，称为“高伽马”波段。高伽马功率可能来自持续振荡（类似于伽马节律，但以更高的频率运行）或来自与电极附近产生的尖峰相关的短暂功率爆发（“尖峰渗血”）。很难将这两个假设分开，因为在大多数刺激或认知操作过程中，伽马振荡和尖峰是相关的。此外，大多数信号处理技术将任何信号分解为一组振荡函数，使得难以表示在尖峰时刻发生的任何瞬态功率波动。我们解决第一个问题，通过使用刺激操纵的伽马振荡和尖峰活动是反相关的，允许解离。为了解决第二个问题，我们使用了一种称为匹配追踪的信号处理技术，它非常适合捕捉瞬态活动。我们发现，伽玛和高伽玛功率成为反相关，这表明不同的生物物理起源。然而，尖峰和高伽马功率仍然紧密相关。因此，宽带高γ活动可能是电极附近神经元放电的一个容易获得和可靠的电生理指标。
High-gamma (80–200 Hz) activity can be dissociated from gamma rhythms in the monkey cortex, and appears largely to reflect spiking activity in the vicinity of the electrode. During cognitive tasks electrical activity in the brain shows changes in power in specific frequency ranges, such as the alpha (8–12 Hz) or gamma (30–80 Hz) bands, as well as in a broad range above ∼80 Hz, called the high-gamma band. The role or significance of this broadband high-gamma activity is unclear. One hypothesis states that high-gamma oscillations serve just like gamma oscillations, operating at a higher frequency and consequently at a faster timescale. Another hypothesis states that high-gamma power is related to spiking activity. Because gamma power and spiking activity tend to co-vary during most stimulus manipulations (such as contrast modulations) or cognitive tasks (such as attentional modulation), it is difficult to dissociate these two hypotheses. We studied the relationship between high-gamma power, gamma rhythm, and spiking activity in the primary visual cortex (V1) of awake monkeys while varying the stimulus size, which increased the gamma power but decreased the firing rate, permitting a dissociation. We found that gamma power became anti-correlated with the high-gamma power, suggesting that the two phenomena are distinct and have different origins. On the other hand, high-gamma power remained tightly correlated with spiking activity under a wide range of stimulus manipulations. We studied this relationship using a signal processing technique called Matching Pursuit and found that action potentials are associated with sharp transients in the LFP with broadband power, which is visible at frequencies as low as ∼50 Hz. These results distinguish broadband high-gamma activity from gamma rhythms as an easily obtained and reliable electrophysiological index of neuronal firing near the microelectrode. Further, they highlight the importance of making a careful dissociation between gamma rhythms and spike-related transients that could be incorrectly decomposed as rhythms using traditional signal processing methods. Electrical activity in the brain often shows oscillations at distinct frequencies, such as the alpha (8–12 Hz) or gamma (30–80 Hz) bands, which have been linked with distinct cognitive states. In addition, changes in power are seen in a broad range above ∼80 Hz, called the “high-gamma” band. High-gamma power could arise either from sustained oscillations (similar to gamma rhythms but operating at higher frequencies) or from brief bursts of power associated with spikes generated near the electrode (“spike bleed-through”). It is difficult to dissociate these two hypotheses because gamma oscillations and spiking are correlated during most stimulus or cognitive manipulations. Further, most signal processing techniques decompose any signal into a set of oscillatory functions, making it difficult to represent any transient power fluctuations that occur at the time of spikes. We address the first issue by using a stimulus manipulation for which gamma oscillations and spiking activity are anti-correlated, permitting dissociation. To address the second issue, we use a signal processing technique called Matching Pursuit, which is well suited to capture transient activity. We show that gamma and high-gamma power become anti-correlated, suggesting different biophysical origins. Spikes and high-gamma power, however, remain tightly correlated. Broadband high-gamma activity could therefore be an easily obtained and reliable electrophysiological index of neuronal firing in the vicinity of an electrode.
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