Principles of multi-whisker stimulus integration in rodent somatosensory cortex
Principles of multi-whisker stimulus integration in rodent somatosensory cortex
批准号:
10358532
负责人:
Keven J Laboy-Juarez
金额:
$8.07万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2017
资助国家:
美国
项目状态:
已结题
起止时间:
2017-09-28 至 2023-02-28
关键词:
AddressAffectAnatomyBehaviorBlindnessBrainBypassCellsCodeCommunicationComplexCortical ColumnCutaneousDataDevelopmentEnvironmentEsthesiaExhibitsFunctional disorderImageLearningMapsMeasuresMethodsModelingMotorMusNeuronsPatternPerceptionPersonsPopulationPostdoctoral FellowPrincipal Component AnalysisProbabilityProcessResearchRodentRoleSensorySignal TransductionSomatosensory CortexStimulusSystemTactileTestingThalamic structureTrainingVibrissaeWorkbasedisabilityexperimental studyextracellularhapticsimprovednovelpost-doctoral trainingpreferencereceptive fieldreceptorrelating to nervous systemresponsesensorsensory inputsensory integrationsensory systemsomatosensoryspatiotemporaltwo-photon
中文摘要
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英文摘要
Project Summary
Integration of sensory signals is crucial for sensory processing in the brain. Rodent whisker somatosensory cortex
(S1) provides a powerful system to study this, because neurons integrate tactile information across a discrete array
of whiskers. S1 circuitry is well characterized, but tactile representation remains poorly understood. Most studies
have focused S1 encoding of single-whisker deflections. This stimuli elicit low-probability spiking, relatively weak
somatotopic tuning, and highly similar receptive fields and maps in thalamus and across cortical layers. This weak-
redundant code suggests that S1 neurons may code for more complex stimuli than single-whisker deflections.
My project tests whether S1 neurons code for multi-whisker stimuli, which are generated during natural whisker
sensation. I propose that multi-whisker tuning is achieved by linear and non-linear integration and that multi-
whisker features are represented in a novel topographic map in S1. Aim 1 describes past work in which I extensively
characterized multi-whisker tuning to 2-whisker sequences, which represent a tractable and important subset of
multi-whisker stimuli. I discovered that many neurons have strong spatiotemporal tuning for specific 2-
whisker sequences at specific inter-whisker-deflection-intervals (Δt). I found that a combination of linear
and nonlinear mechanisms construct and enhance spatial selectivity, with prominent sublinear suppression of
non-preferred stimuli. I also discovered principles governing Δt tuning and that it enhances spatial selectivity
for 2-whisker sequences, thus defining general computations underlying multi-whisker integration
In Aim2, I will use 2-photon Ca2+ imaging to determine the representation of 2-whisker sequences at the population
level. While neurons in L2/3 of S1 are highly intermixed by single-whisker tuning (Sato et al. 2007, Clancy KB et al.
2015), I propose that discrete cortical columns will be apparent if receptive fields are defined in terms of 2-whisker
sequences. My results suggest that the edges of each column will be defined by a ring of spatiotemporally selective
neurons that form discrete borders between columns through sharp differences in Δt tuning. Also, by imaging many
neurons simultaneously, I will test whether firing correlations between spatiotemporally selective and non-selective
units provide a robust population level code for 2-whisker sequences. This will greatly strengthen our understanding
of how S1 represents multi-whisker stimuli. In Aim 3, I plan to extend my study of active sensory systems by studying
the role of motor circuits in perception during active sensation. Overall, my research plan will contribute significantly
to understanding how the brain integrates sensory and motor signals to generate accurate percepts of the world.
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