Neural Mechanisms for Flexible Vocal Communication
Neural Mechanisms for Flexible Vocal Communication
批准号:
10658308
负责人:
ARKARUP BANERJEE
金额:
$211.91万
依托单位国家:
美国
项目类别:
财政年份:
2023
资助国家:
美国
项目状态:
未结题
起止时间:
2023-05-03 至 2026-04-30
关键词:
Adaptive BehaviorsAnimalsAreaBar CodesBehaviorBehavioralBiologicalBody SizeBrainBrain MappingCallithrixCellsCentral AmericaChronicCollaborationsCommunicationCommunication impairmentComplementComputer ModelsDataDrosophila genusElectrophysiology (science)EvolutionGene ExpressionGoalsHealthHumanIndividualInteractive CommunicationLesionMammalsMapsMasticationMeasuresMethodsMolecularMonitorMotorMotor CortexMotor outputMovement DisordersMusNeurodevelopmental DisorderNeuronsNeurosciencesParkinson DiseasePatternPopulationPrimatesProductionResolutionRodentRodent ModelRoleScienceSiliconSliceSocial EnvironmentSocial InteractionSocial WorkStereotypingSystemTestingTimeUltrasonicsViralVisualWorkautism spectrum disordercomparativedensityexperimental studyflexibilityforestinnovationinsightmotor controlmotor learningneuralneural circuitneuromechanismneurophysiologynoveloptogeneticsorofacialresponsesensory inputsocialsocial communicationsoundstroke-induced aphasiavirtualvocal controlvocalizationzebra finch
中文摘要
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英文摘要
Project Summary:
Whether to laugh at a joke or to engage in a lively debate, we flexibly modify our vocalizations based
upon social contexts. Such adaptive behavior requires real-time adjustments of motor outputs in
response to rapidly changing sensory inputs. How does the brain accomplish this sensorimotor feat?
Pioneering studies have characterized the brain areas responsible for sound production in many
species (e.g., drosophila, zebra finches, marmosets, mice), but the neural circuits that generate vocal
flexibility remain poorly understood. Vocal flexibility, such as during a conversation, requires voluntary,
context-dependent control over sound production. In mammals, based on human brain lesions, gene
expression profiles, and neurophysiology data in primates, cortical control has been proposed to exert
volitional control over sound production. However, direct evidence for this idea is scarce and the neural
circuit-level mechanisms underlying vocal flexibility, especially in mammals, remain largely unknown.
Finding an appropriate rodent model would complement prior work in the primates and would permit
circuit-level mechanisms to be deciphered. Alston’s singing mice (S. teguina), a highly vocal rodent
from the cloud forests of Central America, are ideally suited to study flexible vocal behaviors. Singing
mice show remarkable vocal flexibility, switching between variable, ultrasonic vocalizations (USVs)
and stereotyped, human-audible songs depending upon social context. In contrast, most rodents
including lab mice (M. musculus) produce only USVs and are not known to participate in vocal
interactions. Singing mice and lab mice are roughly the same body size, and brain slices of S. teguina
at a first glimpse is indistinguishable from those of M. musculus. Neural circuit differences underlying
such drastic behavioral divergence are unknown. Here we propose to test whether the ability of the
singing mice to apply vocalizations flexibly within a social context, and lack thereof in most other rodent
species, is dependent upon motor cortical function, acting via downstream vocal production circuits.
Using chronic electrophysiology (Aim 1), single-cell comparative connectomics (Aim 2), we will
determine the role of motor cortex during natural vocal behaviors and compare cortical connectivity
and function between two species. In Aim 3, we will manipulate the circuit to determine their causal
role in various vocal behaviors in each species. By mapping, measuring and manipulating cortical
circuits, we will learn how motor cortex modulates behavioral flexibility in service of social
communication. More broadly, these experiments will provide a systems-level framework to study
hierarchical motor control circuits – for e.g., how high-level (cortical) control can inform low-level
controllers (subcortical pattern-generators) to generate appropriate motor commands – a challenge
faced by biological and artificial agents moving through the world.
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