Circuit mechanisms of self-organized cognitive strategies

自组织认知策略的回路机制

基本信息

批准号：
10337212
负责人：
Erin L Rich
金额：
$ 45.15万
依托单位：
ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI
依托单位国家：
美国
项目类别：
财政年份：
2020
资助国家：
美国
起止时间：
2020-02-05 至 2025-01-31
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10337212
关键词：
Affect Animal Model Area Artificial Intelligence Basal Ganglia Behavior Binding Brain Code Cognition Cognition Disorders Cognitive Cognitive deficits Complex Computer Models Corpus striatum structure Coupling Data Disease Expert Systems Frequencies Functional disorder Goals Grouping Human Impairment Intervention Laboratories Lead Learning Light Location Macaca Macaca mulatta Measures Mediating Memory Memory impairment Mental disorders Methods Mind Monkeys Motor Neurons Patients Performance Periodicity Play Population Prefrontal Cortex Primates Problem Solving Process Psychology Recurrence Research Resources Role Schizophrenia Short-Term Memory Shorthand Signal Transduction Site Social Security Number Stimulus Structure Synapses System Systematic Bias Telephone Testing Time Visual Work behavior test biological systems cognitive ability cognitive enhancement cognitive function cognitive task cost density experimental study flexibility improved information organization innovation insight language comprehension memory recall microstimulation neuromechanism neurophysiology neuroregulation nonhuman primate novel novel strategies relating to nervous system tool

项目摘要

Project Summary Decades of psychology research have shown that working memory is limited, and humans can only hold a few items in mind at the same time. However, cognitive tasks like planning and problem solving require access to many pieces of information at once. To overcome this constraint, we enlist mnemonic strategies, for instance grouping pieces of information into chunks, as we commonly do to remember telephone or social security numbers. Mnemonic chunking allows us to flexibly organize information on line, providing a fundamental building block for advanced cognitive abilities. Chunking impairments occur when damage or dysfunction involves the dorsolateral prefrontal cortex (dlPFC), for instance in patients with schizophrenia, and severely compromises overall cognitive function. Thus, determining how the brain organizes information is a necessary step toward understanding the mechanisms of advanced cognition, and how these go awry in disease states. A key challenge is that strategies for organizing information are self-generated and highly variable in a laboratory setting. A central innovation of this proposal is the novel computational approach used to identify spontaneous mnemonic chunking in macaque monkeys. This is critical because animal models allow us to interrogate brain function with advanced neurophysiological tools. Here, we will use high-density, multi-site recording and targeted neuromodulation to understand the circuit mechanisms that chunk mnemonic information. Previous theoretical work suggests that chunks arise from compressed working memory representations that act as neural shorthand, economizing on processing resources at the cost of degrading some original information. Neurons in dlPFC encode items in working memory, and their dynamics are shaped by recurrent interactions with the basal ganglia. Thus, we hypothesize that corticostriatal interactions promote the efficient reorganization of working memory that underlies chunking. To test this we will investigate dlPFC- striatal dynamics when monkeys spontaneously chunk information in a self-organized working memory task. We will record large numbers of single neurons and local field potentials, and dynamically decode representations held in working memory to assess how mnemonic codes and corticostriatal interactions change when items are or are not chunked. In addition, exogenous stimulation will test the causal role of striatal circuits in promoting the formation of mnemonic chunks. Together, these experiments will determine how the brain establishes mnemonic chunks to optimize working memory performance. This will shed light on a fundamental feature of advanced cognition, and how dysfunction in these mechanisms could give rise to disorders of thought and memory. Finally, understanding mechanisms that optimize cognitive function in a biological system may fuel creative advances that optimize performance in artificial intelligence systems.

项目概要几十年的心理学研究表明，工作记忆是有限的，人类只能记住几个同时记住的项目。然而，诸如计划和解决问题之类的认知任务需要访问一次获得许多信息。为了克服这个限制，我们采用助记策略，例如将信息分成大块，就像我们通常记住电话或社会保险一样数字。助记词分块使我们能够灵活地在线组织信息，为我们提供了基础高级认知能力的基石。当损坏或功能障碍时就会发生组块损伤涉及背外侧前额皮质（dlPFC），例如精神分裂症患者，并且严重损害整体认知功能。因此，确定大脑如何组织信息是必要的朝着理解高级认知机制以及这些机制在疾病状态下如何出错的方向迈出了一步。一个关键的挑战是，组织信息的策略是自我生成的，并且在不同的环境中变化很大。实验室设置。该提案的一个核心创新是用于识别的新颖计算方法猕猴的自发记忆组块。这很重要，因为动物模型使我们能够使用先进的神经生理学工具询问大脑功能。在这里，我们将使用高密度、多站点记录和有针对性的神经调节，以了解记忆组块的电路机制信息。先前的理论工作表明，块是由压缩的工作记忆产生的作为神经速记的表示，以降级为代价节省处理资源一些原始信息。 dlPFC 中的神经元对工作记忆中的项目进行编码，并且它们的动态被塑造通过与基底神经节的反复相互作用。因此，我们假设皮质纹状体相互作用促进工作记忆的有效重组是分块的基础。为了测试这一点，我们将研究 dlPFC- 当猴子在自组织工作记忆任务中自发地对信息进行组块时，纹状体的动态变化。我们将记录大量的单个神经元和局部场电位，并动态解码工作记忆中保存的表征，用于评估助记码和皮质纹状体如何相互作用当项目被分块或不被分块时会发生变化。此外，外源刺激将测试因果作用纹状体回路促进记忆块的形成。这些实验将共同决定大脑如何建立助记块来优化工作记忆性能。这将揭示高级认知的基本特征，以及这些机制的功能障碍如何导致思维和记忆障碍。最后，了解优化认知功能的机制生物系统可能会推动创新进步，从而优化人工智能系统的性能。