Auditory processing: The cellular and synaptic mechanisms of a delay-line and coincidence-detector circuit

听觉处理：延迟线和重合检测器电路的细胞和突触机制

• 批准号: BB/P022111/1
• 负责人: Berthold Hedwig
• 金额: $ 50.92万
• 依托单位: University of Cambridge
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2017
• 资助国家: 英国
• 起止时间: 2017 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=BB%2FP022111%2F1
• 关键词: Auditory; processing; cellular; synaptic; mechanisms

Animals across a wide range of species communicate with acoustic signals composed of simple repetitive patterns of sound pulses like frogs and many insects do. Such simple processes of pattern recognition are essential elements to more complex auditory communication including human speech and also music.Sound however, has a very transient nature. The nervous system must be able to process sequences of signals spread across time to detect their temporal pattern in order to identify a meaning. The four pulses, that form the letter "H" in Morse code, are very similar to the 4 pulses that female crickets orient to, when they are attracted by the calling song of a male. How can the very different nervous systems process and detect such patterns? The computational challenge is very similar across species. When nervous systems of different animals perform a similar task, the nerve cells and neural networks show very similar adaptations. For the processing of temporal sound sequences, researchers analysing different animals came up with very similar concepts. Their idea is that delay-lines and coincidence-detectors would be ideal neuronal circuits to address the question of temporal processing. What does this mean? Let's look at the 4 pulses of the letter "H" in Morse code, which may be separated by a time interval of 50 ms. In the nervous system the auditory signal is split into two pathways. One pathway forwards the information directly to a coincidence detector, the other pathway uses a neuron that imposes a delay of 50 ms on the signal. The consequence is very simple: When the first pulse is processed, it will arrive at the coincidence-detector with no other matching signal; the detector will not be activated. When the second pulse of the Morse signal is processed, the delayed signal from the first pulse and the direct signal to the second pulse will coincide at the detector and elicit a strong response. Summing the coincidence-detector responses over time, can drive feature detectors with activity representing signals of a very specific pattern. In complex brains like ours, thousands of such delay-lines and coincidence-detectors are likely arranged to detect sound signals of different intervals and patterns and form the basis for the perception of rhythms in language and music. These neural circuits are notoriously difficult to study, and no one neuron can be identified in one animal to the next. Some invertebrates, with simpler nervous systems such as the cricket, offer the chance to deeper understand neural processing because delay-line and coincidence-detector circuits can be analysed at the level of identified neurons. We can therefore thoroughly analyse spike and synaptic activity and their network properties across many individuals. We have already characterised the key components of the circuit in the cricket brain, like the delay-line neuron, the coincidence-detector neuron and the feature detector. This circuit is tuned towards the pulse intervals of the cricket song, but how is the duration of pulses detected and how is the overall chirp pattern of the song processed? These are questions that we will address by recording the activity of the circuit neurons and testing them with specific sound patterns that we have already used to characterise the auditory preferences of the females. If we find activity patterns that match the behavioural preferences, then these will allow us to explain how the tuning of the circuit to pulse durations and chirp patterns is established. This will complete our understanding of the processing of temporal patterns at two very different time scales. We will then explore how the pattern recognition circuit leads to the control of female auditory behaviour by identifying and analysing descending neurons that initiate and maintain auditory orientation behaviour.

许多物种的动物通过由简单重复的声音脉冲模式组成的声学信号进行交流，就像青蛙和许多昆虫一样。这种简单的模式识别过程是包括人类语音和音乐在内的更复杂的听觉交流的基本要素。神经系统必须能够处理跨时间传播的信号序列，以检测它们的时间模式，以便识别意义。这四个脉冲，在莫尔斯电码中形成字母“H”，非常类似于雌性蟋蟀被雄性蟋蟀的叫声吸引时的4个脉冲。不同的神经系统如何处理和检测这些模式？计算挑战在不同物种之间非常相似。当不同动物的神经系统执行类似的任务时，神经细胞和神经网络表现出非常相似的适应性。对于时间声音序列的处理，研究人员分析了不同的动物，得出了非常相似的概念。他们的想法是，延迟线和重合探测器将是解决时间处理问题的理想神经元电路。这是什么意思？让我们来看看莫尔斯码中字母“H”的4个脉冲，它们可能被50 ms的时间间隔分开。在神经系统中，听觉信号被分成两条通路。一条通路将信息直接转发到符合检测器，另一条通路使用对信号施加50 ms延迟的神经元。结果非常简单：当第一个脉冲被处理时，它将到达重合检测器，没有其他匹配信号;检测器将不会被激活。当处理莫尔斯信号的第二脉冲时，来自第一脉冲的延迟信号和到第二脉冲的直接信号将在检测器处重合，并引起强响应。随着时间的推移对符合检测器响应进行求和，可以驱动具有表示非常特定模式的信号的活动的特征检测器。在像我们这样复杂的大脑中，成千上万的延迟线和巧合探测器可能被安排来检测不同间隔和模式的声音信号，并形成感知语言和音乐节奏的基础。这些神经回路是出了名的难以研究，没有一个神经元可以在一只动物身上被识别出来。一些神经系统较简单的无脊椎动物，如蟋蟀，提供了更深入了解神经处理的机会，因为可以在已识别的神经元水平上分析延迟线和重合检测器电路。因此，我们可以彻底分析许多个体的尖峰和突触活动及其网络特性。我们已经描述了板球大脑回路的关键组成部分，如延迟线神经元，巧合检测神经元和特征检测器。这个电路被调谐到板球歌曲的脉冲间隔，但是如何检测脉冲的持续时间以及如何处理歌曲的整体啁啾模式？这些问题我们将通过记录回路神经元的活动来解决，并用特定的声音模式来测试它们，我们已经用这些声音模式来测试女性的听觉偏好。如果我们发现了与行为偏好相匹配的活动模式，那么这些将使我们能够解释电路如何根据脉冲持续时间和啁啾模式进行调谐。这将完成我们对两个非常不同的时间尺度上的时间模式处理的理解。然后，我们将探讨模式识别电路如何导致女性听觉行为的控制，通过识别和分析下行神经元，启动和维持听觉定向行为。

项目成果

Phonotactic steering and representation of directional information in the ascending auditory pathway of a cricket.

蟋蟀上升听觉通路中的语音定向和方向信息的表示。

• DOI: 10.1152/jn.00737.2019
• 发表时间: 2020
• 期刊: Journal of neurophysiology
• 影响因子: 2.5
• 作者: Lv M

Song pattern recognition in crickets based on a delay-line and coincidence-detector mechanism.

• DOI: 10.1098/rspb.2017.0745
• 发表时间: 2017-05-31
• 期刊: Proceedings. Biological sciences
• 作者: Hedwig B;Sarmiento-Ponce EJ
• 通讯作者: Sarmiento-Ponce EJ

An auditory-responsive interneuron descending from the cricket brain: a new element in the auditory pathway.

• DOI: 10.1007/s00359-022-01577-8
• 发表时间: 2022-11
• 期刊: Journal of comparative physiology. A, Neuroethology, sensory, neural, and behavioral physiology

A small, computationally flexible network produces the phenotypic diversity of song recognition in crickets.

• DOI: 10.7554/elife.61475
• 发表时间: 2021-11-11
• 期刊: eLife
• 影响因子: 7.7
• 作者: Clemens J;Schöneich S;Kostarakos K;Hennig RM;Hedwig B
• 通讯作者: Hedwig B

Tolerant pattern recognition: evidence from phonotactic responses in the cricket Gryllus bimaculatus (de Geer).

• DOI: 10.1098/rspb.2021.1889
• 发表时间: 2021-12-22
• 期刊: Proceedings. Biological sciences
• 作者: Bent AM;Hedwig B
• 通讯作者: Hedwig B