Identify the schemata by which subcortical signals influence frontal cortical dynamics and cognitive behaviors

识别皮层下信号影响额叶皮层动态和认知行为的图式

• 批准号: 10546515
• 负责人: Karel Svoboda
• 金额: $ 63.72万
• 依托单位: ALLEN INSTITUTE
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-01-15 至 2026-12-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10546515
• 关键词: Anterior; Area; Automobile Driving; Axon; Basal Ganglia; Behavior; Behavioral; Body Weight Changes; Brain region; Calibration; Cell Nucleus; Cerebellum; Cognition Disorders; Cognitive; Coma; Complex; Coupled; Data; Data Science Core; Devices; Disease; Electrophysiology (science); Future; Globus Pallidus; Goals; Head; Hypersomnias; Intralaminar Nuclear Group; Lateral; Left; Link; Logic; Maintenance; Maps; Measurement; Medial; Medial Dorsal Nucleus; Mediating; Medical; Memory; Methods; Midbrain structure; Modeling; Modernization; Molecular; Motor; Motor Cortex; Movement; Multivariate Analysis; Mus; Neurons; Pattern; Phase; Population; Prefrontal Cortex; Reagent; Recurrence; Research Project Grants; Rewards; Role; Science; Sensory; Short-Term Memory; Signal Transduction; Site; Statistical Methods; Structure; Substantia nigra structure; Synapses; Testing; Thalamic structure; Time; Update; Viral; density; dynamic system; excitatory neuron; experience; experimental study; flexibility; frontal lobe; motor disorder; neural; neural circuit; neural patterning; neurophysiology; optogenetics; predictive modeling; response; restraint

Summary, Project 4 (Identify the schemata by which subcortical signals influence frontal cortical dynamics and cognitive behaviors) This research project is focused on dynamic interactions between subcortical areas and frontal cortex via thalamus during flexible behavior. Frontal cortex, including motor cortex and medical prefrontal cortex, displays complex patterns of neural activity that correlate with behavior. These patterns can be decomposed into activity modes (i.e. subspaces in activity space), such as the persistent activity correlated with short-term memory, and the rapidly modulated activity associated with voluntary movements. Complex behaviors correspond to sequences of cortical activity modes. Frontal cortex is tightly coupled with higher-order (non-sensory) thalamus to mediate behavior. Thalamus in turn receives driving input from the basal ganglia the and other subcortical structures. We test the hypothesis that different subcortex inputs to specific thalamic regions control different aspects of cortical activity, including setting the time periods when short-term memories are maintained, the transitions from motor planning to movement execution (Aim 1), and updating and maintaining the values of specific actions during foraging. Our modeling framework (Overall, Project 5) links the dynamical systems perspective of neural computation with actual multi-regional neural circuits and makes predictions that can be tested with neurophysiology. We employ two behavioral tasks in mice that engage well-defined but distinct cortical activity modes. In a memory-guided response task, neurons in the anterior lateral motor cortex (ALM) show preparatory activity, which predicts specific future movements. Just before the onset of movement, preparatory activity collapses in favor of activity modes that drive movement. In a dynamic foraging task, neurons in the medial prefrontal cortex (mPFC) show slowly varying activity patterns that correlate with the value of one action compared to another. This activity is updated based on new information, such as the size of a reward. Projects 1 - 3 provide information about the circuits linking subcortical areas, thalamus, and ALM / mPFC. Building on these circuit mapping experiments we will perform simultaneous recordings from connected subcortex → thalamus → cortex circuits using new multi-shank Neuropixels probes with 5120 recording sites (Project 3). We will combine these recordings with optogenetic manipulations of subcortex and modern multi-variate analysis methods (Data Science Core) to track how subcortical signals propagate through the thalamus into cortex. In the memory-guided response task we will probe the role of the substantia nigra reticulata, acting via the ventromedial nucleus, on maintenance of movement planning, and the impact of midbrain movement centers (e.g. pedunculopontine nucleus), acting via the posterior mediodorsal nucleus, on switching from movement planning to movement initiation (Aim 1). In the foraging task, we will probe how error prediction signals, for example from ventral pallidum (PALv), update memory-related activity in the mPFC via anterior mediodorsal thalamus. These measurements will test key model predictions and in turn inform multi-regional circuit models of cognitive behavior.

项目4总结(识别皮层下信号影响的图式