Malone Brian J, Scott Brian H, Semple Malcolm N
Department of Otolaryngology-Head and Neck Surgery, University of California, San Francisco, California;
Laboratory of Neuropsychology, National Institute of Mental Health/National Institutes of Health, Bethesda, Maryland; and.
J Neurophysiol. 2015 Apr 1;113(7):2934-52. doi: 10.1152/jn.01054.2014. Epub 2015 Feb 18.
The temporal coherence of amplitude fluctuations is a critical cue for segmentation of complex auditory scenes. The auditory system must accurately demarcate the onsets and offsets of acoustic signals. We explored how and how well the timing of onsets and offsets of gated tones are encoded by auditory cortical neurons in awake rhesus macaques. Temporal features of this representation were isolated by presenting otherwise identical pure tones of differing durations. Cortical response patterns were diverse, including selective encoding of onset and offset transients, tonic firing, and sustained suppression. Spike train classification methods revealed that many neurons robustly encoded tone duration despite substantial diversity in the encoding process. Excellent discrimination performance was achieved by neurons whose responses were primarily phasic at tone offset and by those that responded robustly while the tone persisted. Although diverse cortical response patterns converged on effective duration discrimination, this diversity significantly constrained the utility of decoding models referenced to a spiking pattern averaged across all responses or averaged within the same response category. Using maximum likelihood-based decoding models, we demonstrated that the spike train recorded in a single trial could support direct estimation of stimulus onset and offset. Comparisons between different decoding models established the substantial contribution of bursts of activity at sound onset and offset to demarcating the temporal boundaries of gated tones. Our results indicate that relatively few neurons suffice to provide temporally precise estimates of such auditory "edges," particularly for models that assume and exploit the heterogeneity of neural responses in awake cortex.
幅度波动的时间相干性是复杂听觉场景分割的关键线索。听觉系统必须准确划分声学信号的起始和结束。我们探究了清醒恒河猴听觉皮层神经元如何以及在多大程度上对门控音的起始和结束时间进行编码。通过呈现其他方面相同但持续时间不同的纯音,分离了这种表征的时间特征。皮层反应模式多种多样,包括对起始和结束瞬变的选择性编码、紧张性放电和持续抑制。尖峰序列分类方法表明,尽管编码过程存在很大差异,但许多神经元仍能稳健地编码音调持续时间。那些在音调结束时反应主要为相位性的神经元以及那些在音调持续期间反应强烈的神经元实现了出色的辨别性能。尽管多种皮层反应模式在有效持续时间辨别上趋同,但这种多样性显著限制了参考所有反应平均或同一反应类别内平均的尖峰模式的解码模型的效用。使用基于最大似然的解码模型,我们证明了单次试验中记录的尖峰序列能够支持对刺激起始和结束的直接估计。不同解码模型之间的比较确定了声音起始和结束时的活动爆发对划分门控音的时间边界的重要贡献。我们的结果表明,相对较少的神经元就足以提供这种听觉“边缘”的时间精确估计,特别是对于那些假设并利用清醒皮层中神经反应异质性的模型。