Neuronal circuits for context-driven bias in auditory categorization

听觉分类中情境驱动偏差的神经元回路

• 批准号: 10440365
• 负责人: Yale E Cohen
• 金额: $ 68.75万
• 依托单位: UNIVERSITY OF PENNSYLVANIA
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-09-15 至 2024-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10440365
• 关键词: Acoustics; Address; Architecture; Auditory; Auditory area; Automobile Driving; BRAIN initiative; Bayesian Modeling; Behavior; Behavioral; Categories; Clinical; Cochlear Implants; Cognition; Complex; Computer Models; Cues; Data; Dependence; Development; Elderly; Electrophysiology (science); Environment; Exhibits; Feedback; Frequencies; Goals; Head; Individual; Interneurons; Life; Mediating; Mental disorders; Modality; Mus; Neurons; Parietal Lobe; Parvalbumins; Patients; Perception; Population; Process; Psychometrics; Research; Role; Schizophrenia; Sensory; Series; Signal Transduction; Somatostatin; Source; Stimulus; Testing; Time; Training; Uncertainty; Vasoactive Intestinal Peptide; Work; auditory categorization; auditory processing; auditory stimulus; autism spectrum disorder; base; cell type; cognitive task; computer framework; design; developmental disease; excitatory neuron; experience; hearing impairment; inhibitory neuron; insight; neuronal circuitry; nonhuman primate; novel; optogenetics; response; sound; statistics

NEURONAL CIRCUITS FOR CONTEXT-DRIVEN BIAS IN AUDITORY CATEGORIZATION In everyday life, because both sensory signals and neuronal responses are noisy, important cognitive tasks, such as auditory categorization, are based on uncertain information. To overcome this limitation, listeners incorporate other types of signals, such as the statistics of sounds over short and long time scales and signals from other sensory modalities into their categorization decision processes. At the behavioral level, such contextual signals bias categorization by shifting the listener's psychometric curve. At the neuronal level, categorization requires a transformation of sensory representation into a representation of category membership that is modulated by these contextual signals. While categorical representations have been found in the cortex, the cell types and neuronal mechanisms supporting the emergence of these representations remains unknown. Furthermore, the mechanisms by which neuronal categorical representations are modulated by contextual signals, giving rise to a behavioral bias, have not been explored. Our goal is to identify the contribution of specific cell types to categorization and to understand the neuronal mechanisms for how contextual signals bias auditory categorization. Multiple studies have demonstrated that neurons in auditory cortex (AC) and the posterior parietal cortex (PPC) are involved in auditory categorization. Based on the well-described circuit architecture of the AC, recent studies, and our preliminary data, we propose a series of hypotheses that delineate the role of excitatory-inhibitory circuits within AC in creating and biasing categorical stimulus representations and for the role of PPC-AC projections in driving the source for the bias signal. To test these hypotheses, we train mice in a two-alternative-forced choice task in which mice categorize the task, associations). frequency of a “target” sound into one of two overlapping categories (“low” or “high”). While mice participate in this we systematically manipulate three bias signals (short-term and long-term stimulus statistics, and cross-modal Thisdesign allows us to frame the cognitive task within a Bayesian framework, which generates formal computational models for the function of specific neuronal cell types that are tested experimentally. behavioral activity. category. in auditory We will combine this and computational framework with electrophysiological recordings and optogenetic manipulations of neuronal First, we will test whether distinct neuronal cell types in AC differentially encode information about stimulus Second, we will test whether and how specific inhibitory neuronal cell types in AC mediate context dependence auditory categorization. Third, we will test whether and how cortico-cortical feedback mediates context dependence in categorization. Aligned with the goals of the BRAIN initiative, our project will deliver a mechanistic framework for a cortical circuit supporting a complex behavior. These results will quantitatively address an important open question to what extent the same or distinct neuronal populations integrate information across multiple temporal scales and across sensory modalities, generalizing or specializing the representation of the bias in categorization.

在听觉分类中，用于上下文驱动偏见的神经元电路 在日常生活中，因为感觉信号和神经元反应都是噪音，所以重要的认知任务，这样 作为听觉类别，基于不确定的信息。为了克服这一限制，听众结合了其他 信号的类型，例如短时和长时间尺度上的声音统计以及其他感觉方式的信号 进入他们的类别决策过程。在行为层面，这种上下文信号偏差类别通过转移 听众的心理测量曲线。在神经元级别，类别需要转换感官表示 分为由这些上下文信号调节的类别成员资格的表示。而分类 在皮层，细胞类型和神经元机制中都发现了表示形式 表示形式仍然未知。此外，神经元分类表示的机制是 尚未探索由上下文信号调节，引起行为偏见。我们的目标是确定 特定细胞类型对类别的贡献以及了解上下文信号的神经元机制 偏见听觉类别。 多项研究表明，听觉皮层（AC）和后顶叶皮层（PPC）中的神经元（PPC） 参与听觉类别。基于AC的描述良好的电路架构，最近的研究和我们的 初步数据，我们提出了一系列假设，这些假设描述了AC在AC中的兴奋性抑制回路的作用 创建和偏见分类刺激表示以及PPC-AC项目在推动来源的作用 偏置信号。为了检验这些假设，我们在两种效力的选择任务中训练小鼠，其中小鼠分类 这 任务， 协会）。 “目标”声音的频率分为两个重叠类别之一（“低”或“高”）。当老鼠参与其中时 我们系统地操纵三个偏置信号（短期和长期刺激统计以及跨模式 此设计使我们能够在贝叶斯框架中构架认知任务，该框架生成正式 经过实验测试的特定神经元细胞类型功能的功能的计算模型。 行为 活动。 类别。 在 听觉 我们将结合起来 以及具有电生理记录和神经元的光学遗传操作的计算框架 首先，我们将测试AC中的不同神经元细胞类型是否差异编码有关刺激的信息 其次，我们将测试AC中的特定抑制性神经元细胞类型是否介导上下文依赖性 听觉类别。第三，我们将测试Cortico-cortical反馈是否介导上下文依赖性 分类。 与大脑计划的目标保持一致，我们的项目将为皮质提供一个机械框架 支持复杂行为的电路。这些结果将在多大程度上定量地解决一个重要的开放问题 相同或不同的神经元种群跨多个临时量表集成了信息 模态，概括或专门对偏见的表示。