Bressler Steven L, Richter Craig G, Chen Yonghong, Ding Mingzhou
Center for Complex Systems and Brain Sciences, Florida Atlantic University, Boca Raton, FL 33431, USA.
Stat Med. 2007 Sep 20;26(21):3875-85. doi: 10.1002/sim.2935.
A framework is presented for quantifying functional network organization in the brain by spectral analysis based on autoregressive modeling. Local field potentials (LFPs), simultaneously recorded from distributed sites in the cerebral cortex of monkeys, are treated as signals generated by local neuronal assemblies. During the delay period of a visual pattern discrimination task, oscillatory assembly activity is manifested in the LFPs in the beta-frequency range (14-30 Hz). Coherence analysis has shown that these oscillations are phase synchronized in functional networks in the sensorimotor cortex in relation to maintenance of contralateral hand position, and in the visual cortex in relation to anticipation of the visual stimulus. Granger causality analysis has revealed information flow in the sensorimotor network that is consistent with a peripheral sensorimotor feedback loop, and in the visual network that is consistent with top-down anticipatory modulation of assemblies in the primary visual cortex.
提出了一个通过基于自回归建模的频谱分析来量化大脑功能网络组织的框架。从猴子大脑皮层的分布式位点同时记录的局部场电位(LFP)被视为由局部神经元集合产生的信号。在视觉模式辨别任务的延迟期,振荡集合活动在β频率范围(14 - 30Hz)的LFP中表现出来。相干分析表明,这些振荡在感觉运动皮层的功能网络中与对侧手位置的维持相关,以及在视觉皮层中与视觉刺激的预期相关,是相位同步的。格兰杰因果分析揭示了感觉运动网络中的信息流与外周感觉运动反馈回路一致,以及视觉网络中的信息流与初级视觉皮层中集合的自上而下的预期调制一致。