Using adaptive psychophysics to identify the neural network reset time in subsecond interval timing.
Using adaptive psychophysics to identify the neural network reset time in subsecond interval timing.
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DOI：
10.1007/s00221-021-06227-0
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发表时间：
2021-12
影响因子：
2
通讯作者：
Terhune DB
中科院分区：
文献类型：
--
作者：
Sadibolova R;Sun S;Terhune DB
亚秒间隔计时的状态依赖网络模型提出，持续时间编码在神经元群体的状态中，这些状态需要在新的计时操作之前重置，以保持最佳的计时性能。先前的研究表明，可以通过改变两个时间间隔之间的刺激间隔来推断该重置间隔的近似边界。然而，这个重置间隔的估计边界很宽（250-500 ms），并且仍然没有明确规定状态依赖网络动态子服务间隔定时的特征。本研究采用自适应心理物理学的方法，对100 ms和200 ms亚秒听觉时长判别任务和对照（音高）判别任务中标准间隔和比较间隔的刺激间隔进行了调整，探讨了重置边界的间隔特异性。我们发现，在两个持续时间判别任务中，当刺激间隔为333 ms时，判别阈值相对于刺激间隔为250 ms时有所提高，而在控制任务中则没有。这一效应证实了先前的研究结果，即亚秒刺激间隔对的识别表现中存在一个断点，它是刺激间延迟增量的函数，但更精确地定位了最小刺激间延迟范围。这些结果表明，服务亚秒定时的状态相关网络需要大约250-333毫秒的时间来重置网络以保持最佳的间隔定时。
State-dependent network models of sub-second interval timing propose that duration is encoded in states of neuronal populations that need to reset prior to a novel timing operation to maintain optimal timing performance. Previous research has shown that the approximate boundary of this reset interval can be inferred by varying the inter-stimulus interval between two to-be-timed intervals. However, the estimated boundary of this reset interval is broad (250–500 ms) and remains under-specified with implications for the characteristics of state-dependent network dynamics sub-serving interval timing. Here, we probed the interval specificity of this reset boundary by manipulating the inter-stimulus interval between standard and comparison intervals in two sub-second auditory duration discrimination tasks (100 and 200 ms) and a control (pitch) discrimination task using adaptive psychophysics. We found that discrimination thresholds improved with the introduction of a 333 ms inter-stimulus interval relative to a 250 ms inter-stimulus interval in both duration discrimination tasks, but not in the control task. This effect corroborates previous findings of a breakpoint in the discrimination performance for sub-second stimulus interval pairs as a function of an incremental inter-stimulus delay but more precisely localizes the minimal inter-stimulus delay range. These results suggest that state-dependent networks sub-serving sub-second timing require approximately 250–333 ms for the network to reset to maintain optimal interval timing.
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