Leveraging multisensory decisions to understand brain wide decision circuits

进球了！这项研究的目的是揭示大脑的广泛回路和局部计算， 使动物能够联合收割机结合多种多样的信息来源， 决策的具体来说，这些实验将研究哺乳动物如何整合 随着时间的推移和跨感觉模态的感觉信号。主要假设是， 除了感觉特定的电路，听觉和视觉决策依赖于共同的核心决策， 用于决策相关计算的电路，例如证据积累和动作选择。 在这些结构中，兴奋性和抑制性神经元之间的靶向连接 支持持续的活动和竞争的行动选择。建议的测试方法 这个假设是测量和操纵老鼠的神经活动， 听觉和视觉刺激的决定。三种方法合在一起构成了 评估这一假设的建议，并提供一个新的观点决策电路。 首先，听觉和视觉决定激活重叠或基本分离的程度 神经结构将基于在脑缺血期间的全皮层活动的宽视野成像来评估。 决策的将在表达钙离子的转基因小鼠中测量全皮质活性。 皮质兴奋性神经元的指标。我们将使用的分类器和决策模型 将大脑结构中的活动与决策计算联系起来。这种方法将 发现在听觉、视觉或多感官决策过程中活跃的候选区域。 接下来，这些候选区域的光遗传学抑制将用于评估它们的因果关系。 在决策中的作用。基于模型的抑制和控制行为比较 试验将评估中断对决策相关计算的影响，例如事件 歧视、证据积累和行动规划。 最后，将调查被确定为特定决策计算的因果关系的区域 更深入地了解这些计算是如何由单个神经元实现的。2- 光子显微镜将用于对单个神经元的群体成像。实验 受试者将是转基因小鼠，其中抑制性神经元发出红色荧光， 独立于用作神经活动估计的绿色荧光。这两 分离的信号使得区分兴奋性神经元和抑制性神经元成为可能， 各自在决策中的作用。单次试验分类器将用于评估 兴奋性和抑制性群体预测动物选择的能力。这场 实验将被用来区分候选模型的决策。

The goal!of the proposed research is to uncover the brain wide circuits and local computations that together allow animals to combine multiple, diverse sources of information to guide decision-making. Specifically, these experiments will investigate how mammals integrate sensory signals over time and across sensory modalities. The main hypothesis is that in addition to sense-specific circuits, auditory and visual decisions rely on common, core decision circuits for decision-related computations, such as evidence accumulation and action selection. Within these structures, targeted connectivity between excitatory and inhibitory neurons supports persistent activity and competition for action selection. The proposed method to test this hypothesis is to measure and manipulate neural activity in mice trained to make perceptual decisions about auditory and visual stimuli. Three approaches, taken together, form the core of the proposal to evaluate this hypothesis and provide a new view of decision-making circuits. First, the degree to which auditory and visual decisions activate overlapping or largely separate neural structures will be evaluated based on wide field imaging of cortex-wide activity during decision-making. Cortex-wide activity will be measured in transgenic mice that express calcium indicators in cortical excitatory neurons. Classifiers and decision-making models we will used to link activity in a given brain structure to decision-making computations. This approach will uncover candidate areas that are active during auditory, visual or multisensory decisions. Next, optogenetic suppression of these candidate areas will be used to evaluate their causal role in decision-making. A model-based comparison of behavior on suppression and control trials will evaluate the effects of disruption on decision-related computations such as event discrimination, evidence accumulation, and action planning. Finally, areas that are identified as causal for specific decision computations will be investigated more closely to understand how these computations are implemented by single neurons. 2- photon microscopy will be used to image populations of single neurons. The experimental subjects will be transgenic mice in which inhibitory neurons emit red fluorescent light that is independent of the green fluorescence that is used as an estimate of neural activity. These two separate signals make it possible to distinguish excitatory from inhibitory neurons and evaluate their respective roles in decision-making. Single-trial classifiers will be used to evaluate the ability of excitatory and inhibitory populations to predict the animal’s choice. The outcome of this experiment will be used to distinguish candidate models of decision-making.