CRCNS: Gradients of receptors underlying distributed cognitive functions

NIMH的一个关键目标是定义复杂行为的机制。这就需要一种方法 这跨越了生物学的范围，但我们一直缺乏一个单一的理论框架来联系 神经递质受体功能，大脑活动和认知的大规模模式。工作记忆是一种 认知的关键组成部分，但我们对工作记忆为什么会出现在 大脑皮质是有限的，但其他的就不是了。猕猴是研究高等认知功能的重要模型 与精神疾病有关，由于他们的聪明行为和相对相似的大脑。我们 提议创建一个高分辨率的猕猴大脑3D图谱，并用它来创建数据驱动的 神经回路模型，将给我们关键的洞察之间的关系，区域差异 受体密度和分布式工作记忆的出现。该地图集将能够量化 14种受体的区域和层状分布(受体指纹)和细胞密度 横跨整个猕猴皮质。这将允许询问受体指纹和细胞密度 精确度低于毫米。它将伴随着一种新的基于梯度的分割方案 整个大脑皮层的细胞和受体结构。这本地图集将登记在尼姆猕猴名下 易于与猕猴/核磁共振数据集成的模板。我们将确定作为基础的主要渐变 受体在大脑皮层的分布，并将其与感觉系统和 使用开放访问的层流束追踪和/MRI数据的认知网络。这种方法将揭示 受体签名是不同功能层次结构的基础。我们将使用以下分支的概念 用数学来询问皮质上受体密度的变化可能会导致 在大脑皮质的特定区域出现类似工作记忆的持续活动。至关重要的是，我们将允许 实验测量的受体密度衡量了每个皮质区域中每个受体的影响。 和层。我们假设，工作记忆活动的模式观察到的跨皮质和 叶层关键地依赖于受体的区域分布。此外，我们将把我们的模型扩展到 包括区域间连接数据，并研究神经调节剂释放如何改变大脑皮层 认知网络之间的活动。我们提议的研究结果可能会大大推进 这一领域的研究，具有广泛的影响。前景看好的初步结果证实了 方法的有效性，确保计划的各个方面都有很高的成功可能性。 相关性(请参阅说明)： 精神疾病的认知症状很难治疗，但可能是患者最大的障碍 独立生活。认知功能依赖于许多大脑区域通过化学物质和 受体，它受精神疾病和药物的影响。我们将绘制这些受体的模式图 所以我们可以建立计算机模型来理解为什么不同大脑的认知功能不同 地区。这可能会导致开发治疗精神疾病认知症状的新疗法。

A key goal of the NIMH is to define the mechanisms of complex behaviors. This necessitates an approach that spans biological scales, but we have been lacking a single theoretical framework that links neurotransmitter receptor function, large-scale patterns of brain activity and cognition. Working memory is a key building block of cognition, but our understanding of why working memory emerges in sorne parts of cortex, but not others, is limited. The macaque is an important model for studying higher cognitive function with relevance to psychiatric disease, due to their intelligent behavior and relatively similar brains. We propose the creation of a high-resolution 3D atlas of the macaque brain, and use it to create data-driven neural circuit models that will give us key insights into the relationship between regional variations in receptor densities and the emergence of distributed working memory. The atlas will enable quantification of the regional and laminar distribution of 14 types of receptors (receptor fingerprints) and cell densities across the entire macaque cortex. This will allow for interrogation of receptor fingerprints and cell densities with submillimeler precision. It will be accompanied by a novel parcellation scheme based on the gradients of cyto- and receptor-architecture across cortex. This atlas will be registered lo the NIMH Macaque Template for easy integration with macaque /MRI data. We will identify the principal gradients that underlie the distribution of receptors across cortex and compare these to hierarchies of sensory systems and cognitive networks using open-access laminar tract-tracing and /MRI data. This approach will uncover the receptor signature underlying distinct functional hierarchies. We will use the idea of bifurcations from mathematics to interrogate how changes lo the density of receptors across cortex may lead to the emergence of working-memory like persistent activity in particular regions of cortex. Crucially, we will allow the experimentally measured receptor densities lo scale the effects of each receptor in each cortical area and layer. We hypothesize that the pattern of working memory activity observed across cortical areas and lamina depends critically on the regional distribution of the receptors. Further, we will expand our model to include inter-areal connectivity data and investigate how release of neuromodulators can shift cortical activity between cognitive networks. The results of our proposed research are likely to significantly advance this area of research, with broad implications. The highly promising preliminary results have confirmed the validity of the approach, ensuring that all aspects of the program have a high likelihood of success. RELEVANCE (See instructions): Cognitive symptoms of mental illnesses are difficult to treat, but can be the biggest impediment to patients living independently. Cognitive functions rely on many brain areas communicating through chemicals and receptors, which are affected by mental illness and medication. We will map the pattern of these receptors in the brain, so we can build computer models to understand why cognitive functions differ across brain regions. This could lead to the development of new treatments for cognitive symptoms in mental illness.