Understanding how the brain functions is one of the grand challenges in modern scientific research. Similar to a computer, a functional brain is composed of hardware and software. The major bottleneck lies in the difficulty to directly observe the brain ‘software’, i.e. the rule and operating information used by the brain that might emerge from pan-neuron/synapse connectome. A recognized strategy for probing the functional connectome is to perform volumetric imaging in brains with high spatiotemporal resolution and deep brain penetration. Among various imaging technologies, optical imaging offers appealing combinations including spatial resolution of sub-micrometer to nanometer, temporal resolution of second to millisecond, penetration depth of millimeter or deeper, and molecular contrast based on the abundant choices of fluorescent indicators. Thus, it is ideal for enabling three-dimensional functional brain mapping of small animal models. In this review, we focus on recent technological advances in optical volumetric imaging, with an emphasis on the tools and methods for enhancing imaging speed, depth, and resolution. The review could serve as a quantitative reference for physicists and biologists to choose the techniques better suited for specific applications, as well as to stimulate novel technical developments to advance brain research.

This paper examines whether changes in US presidential administration and central bank turnover during the period 1976–2016 caused regime shifts in Taylor rule deviations. Using a dynamic stochastic general equilibrium model to construct the welfare-maximizing policy rule and deviations from the optimal rule, we find evidence that politics indeed play a key role in explaining these deviations. In addition to politics, unemployment rates and the interest rate spread significantly account for regime shifts in Taylor rule deviations.

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This paper examines whether politics causes regime shifts in deviations from the optimal monetary policy in the United Kingdom. After using a dynamic stochastic general equilibrium model to construct the welfare-maximizing policy rule and deviations from the optimal Taylor rule, we show that politics doe indeed play an important role in explaining these deviations. In addition to politics, unemployment rates account for regime shifts in the Taylor rule deviations.