Circuits for contextual modulation in V1
Circuits for contextual modulation in V1
批准号:
10231007
负责人:
MASSIMO SCANZIANI
金额:
$36.51万
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:
2018-09-15 至 2023-06-30
关键词:
AddressAffectAnatomyAnimalsAreaBehavioralBiological ModelsBrainCalciumCellsColorComputer ModelsD CellsDataData AnalysesElementsFrequenciesHumanImageIn VitroLaser Scanning MicroscopyModelingMusNeuronsPatternPerceptionPhotic StimulationPhotonsProcessPropertyPsychophysicsPyramidal CellsResearch Project GrantsRetinaRoleSensorySomatostatinSourceStimulusStructureTechniquesTestingThalamic structureV1 neuronVasoactive Intestinal PeptideVisualVisual CortexVisual PerceptionWhole-Cell Recordingsarea striataawakebasecalcium indicatorexperimental studyfallsin vivoin vivo calcium imaginginhibitory neuronmillisecondneurophysiologyoptogeneticspredicting responsereceptive fieldresponsespatiotemporaltemporal measurementtwo-photonvisual informationvisual processvisual processingvisual stimulus
中文摘要
我们目前对初级视觉皮质(V1)感觉表征的机械理解是
主要是“前馈”。即V1的感受野(RF)的时空结构
神经元是由早期阶段传递的感受区元素组合而成的
视觉处理(即视网膜和丘脑),以前馈方式。在计算时
基于对V1的这种前馈理解的模型在预测
神经元对视觉刺激的反应出现在神经元的RF边界内,他们
当刺激超过射频的尺寸时,通常会失败,就像日常视觉的情况一样
覆盖整个视野的场景。不能产生电流的主要原因之一
预测V1神经元对自然刺激反应的模型是
他们射频中的V1到刺激强烈地受到他们射频之外发生的事情的调制。换句话说,
V1中的神经元如何对其RF中呈现的刺激做出反应取决于上下文或
“环绕”,在这个范围内,刺激被呈现。在自然界中,视觉刺激落在
V1神经元的Rf从不缺少周围环境。与这些神经生理学相一致
在人类和动物中的观察和心理物理实验表明,对
视觉刺激取决于它与周围视觉环境的关系。因此,能够
依赖于上下文来处理视觉信息是视觉皮质的一个关键属性,并且具有
对我们感知世界的方式产生了深刻影响。只有明确的机械性、电路级
理解语境如何调节V1的反应将使我们能够生成真实的
能够准确预测这一地区对自然刺激的反应的模型。
神经生理学数据表明,V1 MOST中神经元反应的上下文调制
可能依赖于大脑皮层内的相互作用。也就是说,虽然V1神经元的经典RF结构
来自前馈过程的结果,由环绕的调制可能取决于内-
大脑皮层电路元件、它们的连接模式及其动态相互作用。这项建议
旨在阐明这些皮质回路元素以及它们的相互作用如何引起
V1中对视觉刺激反应的语境调制。彻头彻尾的机械主义者
理解V1中的上下文调制将使我们能够构建能够
捕捉视觉皮质对自然刺激的反应。因此,从这一过程中获得的数据
在告知和验证V1的现实模型时,建议书将至关重要。
英文摘要
Our current mechanistic understanding of sensory representation in primary visual cortex (V1) is
principally “feed-forward”. That is, the spatio-temporal structure of the receptive field (RF) of V1
neurons results from the combination of receptive filed elements transmitted by earlier stages of
visual processing (i.e. retina and thalamus), in a feed-forward manner. While computational
models based on this feed-forward understanding of V1 are relatively accurate at predicting the
response of neurons to visual stimuli presented within the borders of the neuron’s RF, they
generally fail when the stimuli exceed the size of the RF, as is the case for every-day visual
scenes that encompass the entire field of view. One of the main reason for the inability of current
models to predict responses of V1 neuron to naturalistic stimuli is that the response of neurons in
V1 to stimuli in their RF is strongly modulated by what happens outside of their RF. In other words,
how neurons in V1 respond to a stimulus presented in their RF depends on the context or
“surround” within which the stimulus is presented. In the natural world, visual stimuli falling in the
RF of a V1 neuron are never devoid of a surround. Consistent with these neurophysiological
observations, psychophysical experiments in humans and animals show that the perception of a
visual stimulus depends on its relationship to the surrounding visual context. Thus, the ability to
process visual information depending on the context is a key property of visual cortex and has a
profound impact on how we perceive the world. Only a clear mechanistic, circuit level
understanding of how the context modulates the response of V1 will allow us generate realistic
models capable of accurately predicting the response of this area to naturalistic stimuli.
Neurophysiological data indicate that contextual modulation of neuronal responses in V1 most
likely relies on intra-cortical interactions. That is, while the classical RF structure of a V1 neuron
results from a feed-forward process, the modulation by the surround likely depends on intra-
cortical circuit elements, their connectivity pattern and their dynamic interactions. This proposal
aims at elucidating these cortical circuit elements and how their interaction gives rise to the
contextual modulation of the response to visual stimuli in V1. A thorough mechanistic
understanding of contextual modulation in V1 will allow us to build realistic models capable of
capturing the response of visual cortex to naturalistic stimuli. Thus, data obtained from this
proposal will be essential in informing and validating realistic models of V1.
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Circuits for contextual modulation in V1
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