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反复神经处理与躯体感觉意识。

Recurrent neural processing and somatosensory awareness.

机构信息

Berlin School of Mind and Brain, Humboldt-Universität zu Berlin, 10099 Berlin, Germany.

出版信息

J Neurosci. 2012 Jan 18;32(3):799-805. doi: 10.1523/JNEUROSCI.3974-11.2012.

Abstract

The neural mechanisms of stimulus detection, despite extensive research, remain elusive. The recurrent processing hypothesis, a prominent theoretical account of perceptual awareness, states that, although stimuli might in principle evoke feedforward activity propagating through the visual cortex, stimuli that become consciously detected are further processed in feedforward-feedback loops established between cortical areas. To test this theory in the tactile modality, we applied dynamic causal modeling to electroencephalography (EEG) data acquired from humans in a somatosensory detection task. In the analysis of stimulation-induced event-related potentials (ERPs), we focused on model-based evidence for feedforward, feedback, and recurrent processing between primary and secondary somatosensory cortices. Bayesian model comparison revealed that, although early EEG components were well explained by both the feedforward and the recurrent models, the recurrent model outperformed the other models when later EEG segments were analyzed. Within the recurrent model, stimulus detection was characterized by a relatively early strength increase of the feedforward connection from primary to secondary somatosensory cortex (>80 ms). At longer latencies (>140 ms), also the feedback connection showed a detection-related strength increase. The modeling results on relative evidence between recurrent and feedforward model comparison support the hypothesis that the ERP responses from sensory areas arising after aware stimulus detection can be explained by increased recurrent processing within the somatosensory network in the later stages of stimulus processing.

摘要

尽管已经进行了广泛的研究,但刺激检测的神经机制仍然难以捉摸。感知意识的一个突出理论解释是,尽管刺激原则上可以引发通过视觉皮层传播的前馈活动,但成为有意识检测到的刺激会在皮层区域之间建立的前馈-反馈回路中进一步处理。为了在触觉模态中测试这一理论,我们应用动态因果建模对人类在体感检测任务中采集的脑电图 (EEG) 数据进行了分析。在对刺激引起的事件相关电位 (ERP) 的分析中,我们专注于基于模型的证据,用于初级和次级体感皮层之间的前馈、反馈和递归处理。贝叶斯模型比较显示,尽管早期 EEG 成分可以很好地用前馈和递归模型来解释,但当分析后期 EEG 段时,递归模型优于其他模型。在递归模型中,刺激检测的特征是从初级体感皮层到次级体感皮层的前馈连接的相对早期强度增加(>80 ms)。在较长的潜伏期(>140 ms),反馈连接也显示出与检测相关的强度增加。递归模型和前馈模型比较的相对证据建模结果支持这样的假设,即从有意识刺激检测中产生的感觉区域的 ERP 反应可以通过刺激处理后期体感网络中递归处理的增加来解释。

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