The planning of new compositional action sequences guided by interpretation of ambiguous sensory data in a novel drawing task

在新颖的绘画任务中通过解释模糊的感官数据来规划新的构图动作序列

• 批准号: 10475124
• 负责人: Lucas Y. Tian
• 金额: $ 7.48万
• 依托单位: ROCKEFELLER UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-09-16 至 2023-09-15
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10475124
• 关键词: Address; Algorithms; Anatomy; Animals; Area; Behavior; Behavioral; Behavioral Mechanisms; Behavioral Model; Behavioral Paradigm; Birds; Brain; Brain Diseases; Clinical Psychology; Cognition Disorders; Cognitive; Cognitive Science; Complex; Data; Disease; Electrophysiology (science); Exhibits; Foundations; Goals; Human; Impairment; Joints; Knowledge; Language; Lead; Learning; Libraries; Link; Literature; Location; Macaca; Maps; Mediating; Mental Processes; Modeling; Motor; Motor Cortex; Neurosciences; Outcome; Primates; Procedures; Process; Psyche structure; Rattus; Research; Sensory; Site; Stroke; Structure; System; Testing; Visual; Vocabulary; base; cognitive capacity; cognitive function; electrical microstimulation; flexibility; frontal lobe; high dimensionality; impaired capacity; innovation; insight; markov model; microstimulation; motor behavior; motor control; neuromechanism; novel; novel strategies; programs; relating to nervous system; spatiotemporal; tool; touchscreen

PROJECT SUMMARY/ABSTRACT Animals exhibit a remarkable array of creative, adaptive, and flexible behaviors. Birds and primates repurpose new materials to build nests and tools; rats efficiently construct navigational shortcuts, and humans generalize knowledge of one language to efficiently speak another. This ability to dynamically create novel behavior “in a single trial” depends on compositional planning, or mental processes that generate strategies by recombining previously learned behavioral components. Crucially, this depends on interpreting ambiguous problems (and associated sensory data) using prior knowledge. There is a dearth of experimental frameworks for studying compositional planning. To address this critical need for new approaches, this proposal will elucidate neural mechanisms in a novel drawing task that I have developed in the Freiwald lab, in which macaques draw copies of never-before-seen visual figures. In contrast to prior studies of action sequences that are memorized or externally guided, in this task drawings must be internally generated and depend on cognitive interpretation of ambiguous sensory data. I will test two central hypotheses: (1) that behavior depends on compositional planning, based on prior knowledge of actions and sequencing rules, and (2) that frontal cortical activity flexibly recombines a “library” of trajectories of neural activity corresponding to actions and rules. The first aim will test the working hypothesis that behavior depends on compositional planning of behavioral programs, or procedures built from a learned vocabulary of actions (i.e., like strokes for “line” or “arc”) and abstract sequencing rules (i.e., higher-order procedures, like “repeat”, “connect”). I will apply unsupervised model-fitting tools to touchscreen and video behavioral data and formally compare alternative models. The second aim is to identify the dynamic neural representations underlying complex drawings by recording large-scale neural activity in frontal cortex. I will test the working hypothesis that novel drawings are represented as combinations of a library of neural activity trajectories encoding actions and sequencing rules. The third aim is to use micro- stimulation to test the working hypothesis that the causal contribution of neural activity towards planning is temporally and anatomically specific in a manner that maps onto the latent structure of behavior. I predict that perturbation of neural trajectories at specific spatio-temporal locations will lead to specific, structured, behavioral perturbations. The expected outcome is an algorithmic account of how neural activity underlies the planning of novel complex actions guided by interpretation of ambiguous sensory data. This is significant because it leads to better understanding of how the brain deploys structured prior knowledge in creative reasoning and behavior. This research is innovative because it introduces a new behavioral paradigm focusing on internally-generated, goal-directed sequences, and integrates concepts and tools from cognitive science with large-scale electrophysiology. This will push the boundaries of our mechanistic understanding of reasoning that is based on internal manipulation of programs and symbolic knowledge.

项目总结/文摘