Department of Neurological Surgery, University of California San Francisco, San Francisco, CA, USA.
Department of Communication Sciences and Disorders, Moody College of Communication, University of Texas at Austin, Austin, TX, USA.
Nat Hum Behav. 2022 Jun;6(6):823-836. doi: 10.1038/s41562-022-01310-0. Epub 2022 Mar 10.
The neurological basis of affective behaviours in everyday life is not well understood. We obtained continuous intracranial electroencephalography recordings from the human mesolimbic network in 11 participants with epilepsy and hand-annotated spontaneous behaviours from 116 h of multiday video recordings. In individual participants, binary random forest models decoded affective behaviours from neutral behaviours with up to 93% accuracy. Both positive and negative affective behaviours were associated with increased high-frequency and decreased low-frequency activity across the mesolimbic network. The insula, amygdala, hippocampus and anterior cingulate cortex made stronger contributions to affective behaviours than the orbitofrontal cortex, but the insula and anterior cingulate cortex were most critical for differentiating behaviours with observable affect from those without. In a subset of participants (N = 3), multiclass decoders distinguished amongst the positive, negative and neutral behaviours. These results suggest that spectro-spatial features of brain activity in the mesolimbic network are associated with affective behaviours of everyday life.
日常生活中情感行为的神经基础还没有被很好地理解。我们从 11 名癫痫患者的中脑边缘网络中获得了连续的颅内脑电图记录，并在手动画出的 116 小时多日视频记录中的自发行为。在个体参与者中，二进制随机森林模型可以从中性行为中以高达 93%的准确率解码出情感行为。积极和消极的情感行为都与中脑边缘网络中高频活动增加和低频活动减少有关。与眶额皮质相比，岛叶、杏仁核、海马体和前扣带回皮质对情感行为的贡献更大，但岛叶和前扣带回皮质对于区分具有可观察到的情感的行为和没有可观察到的情感的行为最为关键。在一部分参与者（N=3）中，多类解码器可以区分积极、消极和中性行为。这些结果表明，中脑边缘网络中脑活动的频谱-空间特征与日常生活中的情感行为有关。
