Control of movements by the cerebellum
小脑对运动的控制
基本信息
- 批准号:10585632
- 负责人:
- 金额:$ 73.61万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2023
- 资助国家:美国
- 起止时间:2023-03-15 至 2027-02-28
- 项目状态:未结题
- 来源:
- 关键词:AlgorithmsAnatomyAnimalsAxonBehaviorBrainCallithrixCell NucleusCellsCerebellar CortexCerebellar DiseasesCerebellar NucleiCerebellar vermis structureCerebellumCodeCollaborationsComplexDataDecelerationDendritesDiseaseDisinhibitionDysmetriaEnsureExhibitsEyeGroupingIndividualInferiorInterneuronsLaboratoriesLearningLightLinkLobuleMacacaMeasuresMolecularMonitorMotionMovementNeuronsNucleus fastigiiOlives - dietaryOutputPathologicPathologic NystagmusPathologyPatternPhasePlayPopulationPrimatesProceduresPropertyPurkinje CellsRoleSaccadesSensorySignal TransductionSiliconStructureSymptomsTechniquesTestingTrainingTremorcell assemblyexperimental studyimprovedinnovationneuralneurophysiologynonhuman primateoptogeneticspopulation basedpreferenceresponsetooltransmission process
项目摘要
Cerebellar disease makes ordinary movements extraordinarily difficult, often resulting in endpoint errors. For
example, damage to lobule VII of the vermis makes saccadic eye movements dysmetric. These symptoms have
suggested that the cerebellum monitors ongoing commands and adjusts them, particularly as the movement nears
the target. Yet, individual Purkinje cells (P-cells) have firing patterns that are modulated much longer than the
movement. Thus, it has been difficult to decode the activities of P-cells, and their downstream nucleus neurons,
with respect to computations that are necessary for control of movements.
A key to this puzzle is that the inferior olive monitors the output of the cerebellum and returns to it
information that appears to encode error [1–4]. This input to the cerebellum organizes P-cells and nucleus neurons
into anatomical groups called micro-clusters [5–7]. Cells within a micro-cluster likely have a common feature: they
respond similarly to error. Through a collaboration between Shadmehr, Soetedjo, and Kojima, we used this idea to
show that in macaques, if P-cells were organized into groups based on their complex spike response to error, then
their simple spikes as a population produced a rate coding that predicted parameters of the ongoing movement
[8,9]. The result was a new idea: the fundamental computational unit in the cerebellum may not be an individual
cell, but a population of cells that share a common preference for error.
Here, we propose that P-cells that respond similarly to error are part of a network that exhibits a special
property: within this network, the P-cells not only coordinate their firing rates, but also temporally align their
spikes, especially during the deceleration phase of movements. That is, P-cells transmit information to the nucleus
by modulating their firing rates, and synchronizing their spikes. In our hypothesis, P-cells combine disinhibition with
synchronization to signal when the movement should be stopped [10]. To pursue this idea, in 2016 we built a
marmoset lab, pioneered techniques to train the animals, and then used silicon probes to record from many
neurons simultaneously [10,11]. We then built new tools for precise temporal analysis of cerebellar spikes [12].
Here, we propose to record from P-cells, molecular layer interneurons (MLIs), and nucleus neurons, use their error
response to organize cells into populations, and then quantify both firing rates and spike timing during movements.
Our proposed experiments have the potential to produce simultaneous recordings of P-cells, MLIs, and
nucleus neurons, something that is unprecedented in primates. We will use this neurophysiological approach to
test the anatomical basis of our hypothesis, that the inferior olive organizes the cerebellum into cell-assemblies.
The data will allow us to determine whether the healthy cerebellum relies on synchronization to encode
information, shedding light on conditions such as dysmetria and tremor, pathologies that appear to arise not from
mis-modulation of P-cell firing rates, but rather disorganization of spike timing [13–16].
小脑疾病使普通运动变得非常困难,经常导致终点错误。为
例如,对蚓部小叶VII的损伤使得扫视眼球运动不规则。这些症状
他认为,小脑会监控正在进行的命令,并调整它们,特别是当运动接近时,
目标.然而,单个浦肯野细胞(P-细胞)的放电模式的调制时间远长于
运动因此,很难解码P细胞及其下游核神经元的活动,
关于控制运动所必需的计算。
解开这个谜团的一个关键是,下橄榄核监控着小脑的输出,并返回到小脑
信息似乎编码错误[1-4]。这一输入到小脑组织P细胞和核神经元
分为称为微簇的解剖组[5-7]。微簇内的细胞可能具有共同的功能:它们
对错误的反应类似。通过Shadmehr、Soetedjo和Kojima之间的合作,我们利用这个想法,
表明在猕猴中,如果P细胞根据其对错误的复杂尖峰反应进行分组,那么
他们作为一个群体的简单尖峰产生了一个速率编码,预测正在进行的运动的参数,
[8,9]。结果产生了一个新的想法:小脑中的基本计算单位可能不是个人
细胞,而是一群共享错误偏好的细胞。
在这里,我们提出,对错误做出类似反应的P细胞是表现出特殊特征的网络的一部分
性质:在这个网络中,P细胞不仅协调它们的放电率,而且在时间上对齐它们的放电率。
特别是在运动的减速阶段。也就是说,P细胞将信息传递到细胞核
通过调节它们的放电频率和同步它们的峰值。在我们的假设中,P细胞结合了联合收割机去抑制和
当运动应该停止时,同步以发出信号[10]。为了实现这个想法,2016年,我们建立了一个
绒猴实验室,开创了训练动物的技术,然后用硅探针记录了许多
神经元同时[10,11]。然后,我们建立了新的工具来精确分析小脑棘波[12]。
在这里,我们建议从P细胞,分子层中间神经元(MLI)和核神经元记录,使用它们的误差
响应,将细胞组织成群体,然后量化运动过程中的放电率和尖峰时间。
我们提出的实验有可能同时记录P细胞、MLI和
这在灵长类动物中是前所未有的。我们将使用这种神经生理学方法,
检验我们假设的解剖学基础,即下橄榄将小脑组织成细胞集合体。
这些数据将使我们能够确定健康的小脑是否依赖于同步编码
信息,阐明诸如辨距障碍和震颤等病症,这些病症似乎不是由
P细胞放电率的错误调节,而是尖峰时间的混乱[13-16]。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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REZA SHADMEHR其他文献
REZA SHADMEHR的其他文献
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{{ truncateString('REZA SHADMEHR', 18)}}的其他基金
A new theory of population coding in the cerebellum
小脑群体编码的新理论
- 批准号:
10005617 - 财政年份:2020
- 资助金额:
$ 73.61万 - 项目类别:
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