Circuitry underlying response summation in mouse and primate: Theory and experiment
Circuitry underlying response summation in mouse and primate: Theory and experiment
批准号:
9975922
负责人:
Nicolas Brunel
金额:
$90.84万
依托单位国家:
美国
项目类别:
财政年份:
2018
资助国家:
美国
项目状态:
已结题
起止时间:
2018-09-30 至 2022-06-30
关键词:
AffectAlzheimer&aposs DiseaseAttentionAutomobile DrivingBehaviorBiological ModelsBiophysicsBrainBrain DiseasesBrain regionCellsCerebral cortexCognitionCollaborationsComplexComputer ModelsConflict (Psychology)DataData SetDependenceDiseaseElementsFailureFeedbackFrequenciesFunctional disorderIndividualInterneuronsLasersLeadMacacaMeasuresMediatingModalityModelingMonkeysMusNeuronsNeurosciencesNeurosciences ResearchNoiseOpsinOutputPatternPerceptionPhotic StimulationPlayPrimatesPropertyResearchRetinaRoleSchizophreniaSensoryShapesSpeedStimulusStructureSynapsesSynaptic plasticityTestingTheoretical modelTimeVariantViralVisualWorkanalytical toolarea striataartificial neural networkautism spectrum disorderawakecell typedriving forceexcitatory neuronexperimental groupexperimental studyinhibitory neuroninsightluminancemultiple datasetsneocorticalnetwork modelsneural circuitneurophysiologyoptogeneticspredictive modelingpublic health relevancereceptive fieldrelating to nervous systemresponsesensory stimulusspecies differencetheoriestoolvisual stimulus
中文摘要
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英文摘要
Project Summary
Despite the enormous complexity of the brain, it is becoming increasingly apparent that structures like the
cerebral cortex are modular, relying on a set of canonical computations that occur across brain regions and
modalities to mediate perception, cognition and behavior. One important example of a canonical computation
is the summation of various driving, contextual, and modulatory neuronal inputs to yield spiking output. The
question of how cortical networks integrate these inputs and transform them into spiking outputs of individual
neurons is of central importance to neuroscience. A significant challenge to understanding these computations
is that each neuron is embedded within a larger circuit of neurons, each modulating one another’s activity. So,
understanding how a particular neuron responds to input necessarily involves understanding the larger circuit.
Recent optogenetic studies have found different patterns of input summation in mouse vs. monkey V1.
Recently developed theoretical models have produced specific predictions about the differences in network
circuitry that can lead to differences in summation, and predict how summation non-linearities depend on
inputs to the network. The proposed research will test these predictions and seek to understand these circuit
computations using a combination of theoretical work and optogenetic modulation of circuits in mouse and
monkey. Aim 1: Varying E and I optogenetic stimulation and visual contrast independently to measure
spike response summation to multiple inputs. In this Aim, theoretical models of input summation across
varying cortical circuit regimes will be developed, and recently developed optogenetic tools will be used in
awake mouse and monkey V1 to test predictions generated by these models and identify the corresponding
regimes. The optogenetic tools include a new viral strategy that directs expression of different opsins to
inhibitory vs. excitatory neocortical neurons in the macaque. Simultaneous and independent activation of E and
I and the visual stimulus, all within this theoretical framework, will enable us to test whether observed
differences in summation properties reflect fundamental species differences or reflect a common computation
operating in different parameter regimes. Aim 2: Determine the circuit elements controlling dynamics of
cortical network responses using dynamic optogenetic stimulation. In this Aim, experiments using
dynamic optogenetic and visual stimulation patterns and theoretical analysis of the models with dynamic inputs
will be used to elucidate the temporal dynamics of summation. Aim 3: Determine if different inhibitory
subclasses control different aspects of input integration. Different inhibitory subclasses will be stimulated
optogenetically to decipher their respective roles in input summation. Taken together, these Aims will help
define the roles played by excitatory and inhibitory neurons in mediating summation of neuronal inputs to yield
spiking output. This information will be critical for understanding brain disorders associated with failures in
perception and attention, as is seen with autism, schizophrenia, and Alzheimer’s disease.
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会议论文
Canonical computations for motor learning by the cerebellar cortex micro-circuit
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批准号:9814049
-
项目类别:
-
资助金额:$129.05万
-
财政年份:2019
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负责人:Nicolas Brunel
-
依托单位:
Canonical computations for motor learning by the cerebellar cortex micro-circuit
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批准号:10155611
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项目类别:
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资助金额:$127.53万
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财政年份:2019
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负责人:Nicolas Brunel
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依托单位:
Canonical computations for motor learning by the cerebellar cortex micro-circuit
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批准号:10614484
-
项目类别:
-
资助金额:$126.43万
-
财政年份:2019
-
负责人:Nicolas Brunel
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依托单位:
Canonical computations for motor learning by the cerebellar cortex micro-circuit
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批准号:9976609
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项目类别:
-
资助金额:$127.53万
-
财政年份:2019
-
负责人:Nicolas Brunel
-
依托单位:
Canonical computations for motor learning by the cerebellar cortex micro-circuit
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批准号:10397037
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项目类别:
-
资助金额:$127.53万
-
财政年份:2019
-
负责人:Nicolas Brunel
-
依托单位:
Large-scale, neuronal ensemble recordings in motor cortex of the behaving marmoset
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批准号:10321250
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项目类别:
-
资助金额:$58.03万
-
财政年份:2018
-
负责人:Nicolas Brunel
-
依托单位:
Circuitry underlying response summation in mouse and primate: Theory and experiment
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批准号:9792300
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项目类别:
-
资助金额:$90.84万
-
财政年份:2018
-
负责人:Nicolas Brunel
-
依托单位:
Large-scale, neuronal ensemble recordings in motor cortex of the behaving marmoset
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批准号:10083242
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项目类别:
-
资助金额:$57.97万
-
财政年份:2018
-
负责人:Nicolas Brunel
-
依托单位:
Learning spatio-temporal statistics from the environment in recurrent networks
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批准号:9170047
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项目类别:
-
资助金额:$40.35万
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财政年份:2016
-
负责人:Nicolas Brunel
-
依托单位: