Suppr超能文献

将行为和感官背景纳入听觉编码的频谱-时间模型。

Incorporating behavioral and sensory context into spectro-temporal models of auditory encoding.

作者信息

David Stephen V

机构信息

Oregon Hearing Research Center, Oregon Health & Science University, 3181 SW Sam Jackson Park Rd, MC L335A, Portland, OR 97239, United States.

出版信息

Hear Res. 2018 Mar;360:107-123. doi: 10.1016/j.heares.2017.12.021. Epub 2017 Dec 31.

Abstract

For several decades, auditory neuroscientists have used spectro-temporal encoding models to understand how neurons in the auditory system represent sound. Derived from early applications of systems identification tools to the auditory periphery, the spectro-temporal receptive field (STRF) and more sophisticated variants have emerged as an efficient means of characterizing representation throughout the auditory system. Most of these encoding models describe neurons as static sensory filters. However, auditory neural coding is not static. Sensory context, reflecting the acoustic environment, and behavioral context, reflecting the internal state of the listener, can both influence sound-evoked activity, particularly in central auditory areas. This review explores recent efforts to integrate context into spectro-temporal encoding models. It begins with a brief tutorial on the basics of estimating and interpreting STRFs. Then it describes three recent studies that have characterized contextual effects on STRFs, emerging over a range of timescales, from many minutes to tens of milliseconds. An important theme of this work is not simply that context influences auditory coding, but also that contextual effects span a large continuum of internal states. The added complexity of these context-dependent models introduces new experimental and theoretical challenges that must be addressed in order to be used effectively. Several new methodological advances promise to address these limitations and allow the development of more comprehensive context-dependent models in the future.

摘要

几十年来,听觉神经科学家一直使用频谱 - 时间编码模型来理解听觉系统中的神经元如何表征声音。从系统识别工具在听觉外周的早期应用衍生而来,频谱 - 时间感受野(STRF)以及更复杂的变体已成为表征整个听觉系统中表征的有效手段。这些编码模型大多将神经元描述为静态的感觉滤波器。然而,听觉神经编码并非静态。反映声学环境的感觉背景和反映听众内部状态的行为背景,都可以影响声音诱发的活动,特别是在中枢听觉区域。这篇综述探讨了将背景整合到频谱 - 时间编码模型中的最新努力。它首先简要介绍了估计和解释STRF的基础知识。然后描述了三项最近的研究,这些研究表征了在从几分钟到几十毫秒的一系列时间尺度上出现的对STRF的背景效应。这项工作的一个重要主题不仅是背景影响听觉编码,而且背景效应跨越了很大范围的内部状态。这些依赖于背景的模型增加的复杂性带来了新的实验和理论挑战,为了有效使用这些模型必须加以解决。一些新的方法进展有望解决这些限制,并在未来允许开发更全面的依赖于背景的模型。

相似文献

1
Incorporating behavioral and sensory context into spectro-temporal models of auditory encoding.
Hear Res. 2018 Mar;360:107-123. doi: 10.1016/j.heares.2017.12.021. Epub 2017 Dec 31.
2
Capturing contextual effects in spectro-temporal receptive fields.
Hear Res. 2016 Sep;339:195-210. doi: 10.1016/j.heares.2016.07.012. Epub 2016 Jul 27.
3
Context dependence of spectro-temporal receptive fields with implications for neural coding.
Hear Res. 2011 Jan;271(1-2):123-32. doi: 10.1016/j.heares.2010.01.014. Epub 2010 Feb 1.
4
Stability of spectro-temporal tuning over several seconds in primary auditory cortex of the awake ferret.
Neuroscience. 2007 Sep 7;148(3):806-14. doi: 10.1016/j.neuroscience.2007.06.027. Epub 2007 Aug 10.
5
Gabor analysis of auditory midbrain receptive fields: spectro-temporal and binaural composition.
J Neurophysiol. 2003 Jul;90(1):456-76. doi: 10.1152/jn.00851.2002. Epub 2003 Mar 26.
7
The Essential Complexity of Auditory Receptive Fields.
PLoS Comput Biol. 2015 Dec 18;11(12):e1004628. doi: 10.1371/journal.pcbi.1004628. eCollection 2015 Dec.
8
Understanding auditory spectro-temporal receptive fields and their changes with input statistics by efficient coding principles.
PLoS Comput Biol. 2011 Aug;7(8):e1002123. doi: 10.1371/journal.pcbi.1002123. Epub 2011 Aug 18.
9
Plasticity of Multidimensional Receptive Fields in Core Rat Auditory Cortex Directed by Sound Statistics.
Neuroscience. 2021 Jul 15;467:150-170. doi: 10.1016/j.neuroscience.2021.04.028. Epub 2021 May 2.
10
Differences between spectro-temporal receptive fields derived from artificial and natural stimuli in the auditory cortex.
PLoS One. 2012;7(11):e50539. doi: 10.1371/journal.pone.0050539. Epub 2012 Nov 27.

引用本文的文献

1
Receptive-field nonlinearities in primary auditory cortex: a comparative perspective.
Cereb Cortex. 2024 Sep 3;34(9). doi: 10.1093/cercor/bhae364.
2
Subcortical origin of nonlinear sound encoding in auditory cortex.
Curr Biol. 2024 Aug 5;34(15):3405-3415.e5. doi: 10.1016/j.cub.2024.06.057. Epub 2024 Jul 19.
3
A sparse code for natural sound context in auditory cortex.
Curr Res Neurobiol. 2023 Nov 29;6:100118. doi: 10.1016/j.crneur.2023.100118. eCollection 2024.
4
Spectral-temporal processing of naturalistic sounds in monkeys and humans.
J Neurophysiol. 2024 Jan 1;131(1):38-63. doi: 10.1152/jn.00129.2023. Epub 2023 Nov 15.
5
naplib-python: Neural acoustic data processing and analysis tools in python.
Softw Impacts. 2023 Sep;17. doi: 10.1016/j.simpa.2023.100541. Epub 2023 Jul 7.
6
Trait anxiety modulates the detection sensitivity of negative affect in speech: an online pilot study.
Front Behav Neurosci. 2023 Sep 7;17:1240043. doi: 10.3389/fnbeh.2023.1240043. eCollection 2023.
9
Cortical adaptation to sound reverberation.
Elife. 2022 May 26;11:e75090. doi: 10.7554/eLife.75090.
10
Neural Substrates and Models of Omission Responses and Predictive Processes.
Front Neural Circuits. 2022 Feb 1;16:799581. doi: 10.3389/fncir.2022.799581. eCollection 2022.

本文引用的文献

1
Focal Suppression of Distractor Sounds by Selective Attention in Auditory Cortex.
Cereb Cortex. 2018 Jan 1;28(1):323-339. doi: 10.1093/cercor/bhx288.
2
Distinct timescales of population coding across cortex.
Nature. 2017 Aug 3;548(7665):92-96. doi: 10.1038/nature23020. Epub 2017 Jul 19.
3
Mapping the Neural Substrates of Behavior.
Cell. 2017 Jul 13;170(2):393-406.e28. doi: 10.1016/j.cell.2017.06.032.
4
Multidimensional receptive field processing by cat primary auditory cortical neurons.
Neuroscience. 2017 Sep 17;359:130-141. doi: 10.1016/j.neuroscience.2017.07.003. Epub 2017 Jul 8.
5
A Corticothalamic Circuit for Dynamic Switching between Feature Detection and Discrimination.
Neuron. 2017 Jul 5;95(1):180-194.e5. doi: 10.1016/j.neuron.2017.05.019. Epub 2017 Jun 15.
6
Feature-Selective Attention Adaptively Shifts Noise Correlations in Primary Auditory Cortex.
J Neurosci. 2017 May 24;37(21):5378-5392. doi: 10.1523/JNEUROSCI.3169-16.2017. Epub 2017 Apr 21.
7
Rapid tuning shifts in human auditory cortex enhance speech intelligibility.
Nat Commun. 2016 Dec 20;7:13654. doi: 10.1038/ncomms13654.
8
Inhibitory control of correlated intrinsic variability in cortical networks.
Elife. 2016 Dec 7;5:e19695. doi: 10.7554/eLife.19695.
9
Attenuation of Responses to Self-Generated Sounds in Auditory Cortical Neurons.
J Neurosci. 2016 Nov 23;36(47):12010-12026. doi: 10.1523/JNEUROSCI.1564-16.2016.
10
Network Receptive Field Modeling Reveals Extensive Integration and Multi-feature Selectivity in Auditory Cortical Neurons.
PLoS Comput Biol. 2016 Nov 11;12(11):e1005113. doi: 10.1371/journal.pcbi.1005113. eCollection 2016 Nov.

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验