P1: Sources and Mechanisms of Sequential Activity
P1: Sources and Mechanisms of Sequential Activity
批准号:
10705963
负责人:
DAVID W TANK
金额:
$33.43万
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
项目状态:
未结题
起止时间:
2023-08-08 至 2028-06-30
关键词:
AnatomyAppearanceArchitectureAreaBRAIN initiativeBehaviorBrainBrain regionCodeCorpus striatum structureCuesDataData ScienceDecision MakingDorsalElectron MicroscopyEtiologyExcisionExhibitsFoundationsGenerationsGeometryHippocampusLateralLevel of EvidenceLocationMedialModelingMusNeocortexNeuroanatomyNeuronsOpticsPhotic StimulationPopulationPositioning AttributePropertyRampRecurrenceResolutionRoleShort-Term MemorySourceStructureTestingTimeWorkentorhinal cortexexperimental studymodel buildingneocorticalnetwork architecturenetwork modelsneuralneural circuitneural modelneural network architectureneuroimagingneuromechanismresponsescaffoldvirtual
中文摘要
项目概要/摘要:项目1,顺序活动的来源和机制
在证据积累过程中,顺序活动在小鼠大脑中广泛存在并占主导地位
决策任务和其他任务。这样的活动可以形成“时间支架”,在其上,其他的活动可以在时间支架上进行。
变量被编码在这些顺序主动响应的幅度中。这项活动,不同于
斜坡和持续的活动往往在知觉决策研究,可以由导航驱动。第一个目标
将通过识别产生序列表征的条件来测试这一想法,例如任务的
时间结构、通过空间位置的导航或视觉刺激。为了区分这些可能性,我们
将记录在任务期间包含顺序活动的区域的神经活动,
功能:主动导航、被动导航和视觉刺激。这项工作将确定是否删除
任务特征的减少消除了连续活动,产生斜坡或持久性。
第二个目标是使用局灶性冷却来测试纹状体作为主颞叶的潜在作用。
脚手架背内侧纹状体(DMS)的中型多刺神经元显示顺序活动。灭活本
区域的提示期有很大的影响,选择,但很少有DMS序列是选择特异性在这一时期。
相反,我们建议DMS产生一个时间支架,控制选择的时间,
新皮层和海马体中的证据编码序列。为了验证这一假设,我们将使用焦点冷却
减缓纹状体神经动力学,同时记录新皮层和海马体。这些结果将限制
序列生成的模型,揭示了顺序神经活动的机制基础。
第三个目标将是通过建立网络架构来确定可以作为观测数据基础的网络架构。
具有三种架构的模型,生成选择性序列。在移动凹凸吸引子模型中,
群体中的活动位置联合编码位置和证据。在竞争链模型中,
证据编码在幅度中,而位置编码在活动位置中,在两个竞争序列中。
在位置-证据乘法模型中,证据在经典的斜坡活动中积累,
随着位置的变化而激活的活动的增加。这些模型将使可测试的实验
预测来帮助我们区分这些网络架构。
第四个目标将是比较超微结构解剖连接与神经编码。我们将使用
行为过程中神经活动的细胞分辨率成像,随后进行连续切片电子显微镜检查,
相同的神经元在背海马和新皮层,经验性地测试网络模型的顺序
活动总之,这个项目的结果将确定任务特征,大脑区域,神经结构,
微观解剖学的基础的外观,时序和功能的顺序活动。我们预计
该项目的实验和模型将大大推进BRAIN计划的三个优先领域:
大脑在活动,证明因果关系,并确定基本原则。
英文摘要
Project Summary/Abstract: Project 1, Sources and Mechanisms of Sequential Activity
Sequential activity is widespread and predominant across the mouse brain during an evidence-accumulation
decision task and in other tasks as well. Such activity may form a “temporal scaffold,” on top of which other
variables are encoded in the amplitude of these sequentially active responses. This activity, different from the
ramps and persistent activity often studied in perceptual decisions, could be driven by navigation. The first aim
will be to test this idea by identifying conditions that produce sequential representations, such as the task’s
timing structure, navigation through spatial locations, or visual stimulation. To distinguish these possibilities, we
will record neural activity from regions containing sequential activity during tasks that isolate these key
features: active navigation, passive navigation, and visual stimulation. This work will establish whether removal
of task features eliminates sequential activity, producing ramps or persistence.
The second aim will be to use focal cooling to test a potential role of the striatum as a master temporal
scaffold. Medium spiny neurons of dorsal medial striatum (DMS) show sequential activity. Inactivation of this
region in the cue period has large effects on choice, yet few DMS sequences are choice-specific in this period.
We propose instead that DMS generates a temporal scaffold that controls the timing of choice and
evidence-encoding sequences in neocortex and hippocampus. To test this hypothesis, we will use focal cooling
to slow striatal neural dynamics, while recording in neocortex and hippocampus. These results will constrain
models of sequence generation and reveal the mechanistic foundations of sequential neural activity.
The third aim will be to identify network architectures that could underlie the observed data, by building
models with three architectures that generate choice-selective sequences. In the moving bump attractor model,
activity location in a population jointly encodes position and evidence. In the competing-chains model,
evidence is encoded in amplitude, while position is encoded in activity location, in two competing sequences.
In the position-evidence multiplicative model, evidence is accumulated in classic ramping activity that controls
the gain of activity that is sequentially activated with position. These models will make testable experimental
predictions to help us distinguish these network architectures.
The fourth aim will be to compare ultrastructural anatomical connectivity with neural coding. We will use
cellular-resolution imaging of neural activity during behavior, followed by serial-section electron microscopy of
the same neurons in the dorsal hippocampus and neocortex, to empirically test network models of sequential
activity. Together, the results of this project will identify task features, brain regions, neural architectures, and
microscale anatomy underlying the appearance, timing, and function of sequential activity. We expect that the
experiments and models in this project will substantially advance three priority areas of the BRAIN Initiative:
the brain in action, demonstrating causality, and identifying fundamental principles.
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