Kinreich Sivan
Psychiatry Department, SUNY Downstate Health Sciences University, Brooklyn, NY, USA.
Transl Psychiatry. 2025 Aug 16;15(1):288. doi: 10.1038/s41398-025-03506-0.
Brain activity is known to be rife with oscillatory activity in different frequencies, which are suggested to be associated with intra-brain communication. However, the specific role of frequencies in neuronal information transfer is still an open question. To this end, we utilized EEG resting state recordings from 5 public datasets. Overall, data from 1668 participants, including people with MDD, ADHD, OCD, Parkinson's, Schizophrenia, and healthy controls aged 5-89, were part of the study. We conducted a running window of Spearman correlation between the two frontal hemispheres' Alpha envelopes. The results of this analysis revealed a unique pattern of correlation states alternating between fully synchronized and desynchronized several times per second, likely due to the interference pattern between two signals of slightly different frequencies, also named "Beating". Subsequent analysis showed this unique pattern in every pair of ipsilateral/contralateral, across frequencies, either in eyes closed or open, and across all ages, underscoring its inherent significance. Biomarker analysis revealed significantly lower synchronization and higher desynchronization for people older than 50 compared to younger ones and lower ADHD desynchronization compared to age-matched controls. Importantly, we propose a new brain communication model in which frequency modulation creates a binary message encoded and decoded by brain regions for information transfer. We suggest that the binary-like pattern allows the neural information to be coded according to certain physiological and biological rules known to both the sender and recipient. This digital-like scheme has the potential to be exploited in brain-computer interaction and applied technologies such as robotics.
众所周知,大脑活动充满了不同频率的振荡活动,这些活动被认为与脑内通信有关。然而,频率在神经元信息传递中的具体作用仍然是一个悬而未决的问题。为此,我们利用了来自5个公共数据集的脑电图静息状态记录。总体而言,该研究纳入了1668名参与者的数据,包括患有重度抑郁症、注意力缺陷多动障碍、强迫症、帕金森病、精神分裂症的患者以及年龄在5至89岁的健康对照者。我们对两个额叶半球的阿尔法包络进行了Spearman相关性的滑动窗口分析。该分析结果揭示了一种独特的相关状态模式,每秒在完全同步和去同步之间交替几次,这可能是由于两个频率略有不同的信号之间的干涉模式,也称为“拍频”。后续分析表明,这种独特模式在每对同侧/对侧、不同频率、闭眼或睁眼以及所有年龄段中均存在,凸显了其内在重要性。生物标志物分析显示,与年轻人相比,50岁以上人群的同步性显著降低,去同步性更高;与年龄匹配的对照组相比,注意力缺陷多动障碍患者的去同步性更低。重要的是,我们提出了一种新的大脑通信模型,其中频率调制创建了一种由脑区编码和解码的二进制消息用于信息传递。我们认为,这种类似二进制的模式允许神经信息根据发送者和接收者都已知的某些生理和生物学规则进行编码。这种类似数字的方案有可能在脑机接口和机器人技术等应用技术中得到应用。