Intracranial EEG-Based Directed Functional Connectivity in Alpha to Gamma Frequency Range Reflects Local Circuits of the Human Mesiotemporal Network.

IF 2.3 3区 医学 Q3 CLINICAL NEUROLOGY Brain Topography Pub Date : 2024-10-22 DOI:10.1007/s10548-024-01084-w
Yulia Novitskaya, Andreas Schulze-Bonhage, Olivier David, Matthias Dümpelmann
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Abstract

To date, it is largely unknown how frequency range of neural oscillations measured with EEG is related to functional connectivity. To address this question, we investigated frequency-dependent directed functional connectivity among the structures of mesial and anterior temporal network including amygdala, hippocampus, temporal pole and parahippocampal gyrus in the living human brain. Intracranial EEG recording was obtained from 19 consecutive epilepsy patients with normal anterior mesial temporal MR imaging undergoing intracranial presurgical epilepsy diagnostics with multiple depth electrodes. We assessed intratemporal bidirectional functional connectivity using several causality measures such as Granger causality (GC), directed transfer function (DTF) and partial directed coherence (PDC) in a frequency-specific way. In order to verify the obtained results, we compared the spontaneous functional networks with intratemporal effective connectivity evaluated by means of SPES (single pulse electrical stimulation) method. The overlap with the evoked network was found for the functional connectivity assessed by the GC method, most prominent in the higher frequency bands (alpha, beta and low gamma), yet vanishing in the lower frequencies. Functional connectivity assessed by means of DTF and PCD obtained a similar directionality pattern with the exception of connectivity between hippocampus and parahippocampal gyrus which showed opposite directionality of predominant information flow. Whereas previous connectivity studies reported significant divergence between spontaneous and evoked networks, our data show the role of frequency bands for the consistency of functional and evoked intratemporal directed connectivity. This has implications for the suitability of functional connectivity methods in characterizing local brain circuits.

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基于颅内脑电图的阿尔法至伽马频率范围的定向功能连接反映了人类中颞网络的局部回路。
迄今为止,用脑电图测量的神经振荡频率范围与功能连通性之间的关系尚不清楚。为了解决这个问题,我们研究了活体人脑中颞中叶和前叶网络结构(包括杏仁核、海马、颞极和海马旁回)之间频率依赖性的定向功能连接。我们连续采集了19名颅内癫痫患者的颅内脑电图记录,这些患者的颞中叶前部磁共振成像正常,正在接受多深度电极的颅内癫痫术前诊断。我们使用格兰杰因果关系(GC)、定向传递函数(DTF)和部分定向相干性(PDC)等几种因果关系测量方法,以特定频率的方式评估了颞内双向功能连通性。为了验证所获得的结果,我们将自发功能网络与通过 SPES(单脉冲电刺激)方法评估的颞内有效连通性进行了比较。通过 GC 方法评估的功能连通性与诱发网络存在重叠,在高频段(α、β 和低伽马)最为突出,但在低频段则消失。通过 DTF 和 PCD 评估的功能连通性具有相似的方向性模式,但海马和海马旁回之间的连通性除外,两者之间的主要信息流方向相反。以往的连通性研究显示,自发网络和诱发网络之间存在显著差异,而我们的数据则显示了频带对功能性颞内定向连通性和诱发颞内定向连通性一致性的作用。这对功能连通性方法在描述局部脑回路特征方面的适用性产生了影响。
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来源期刊
Brain Topography
Brain Topography 医学-临床神经学
CiteScore
4.70
自引率
7.40%
发文量
41
审稿时长
3 months
期刊介绍: Brain Topography publishes clinical and basic research on cognitive neuroscience and functional neurophysiology using the full range of imaging techniques including EEG, MEG, fMRI, TMS, diffusion imaging, spectroscopy, intracranial recordings, lesion studies, and related methods. Submissions combining multiple techniques are particularly encouraged, as well as reports of new and innovative methodologies.
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