Optical imaging techniques reflect different biochemical processes in the brain, which is closely related with neural activity. Scientists and clinicians employ a variety of optical imaging technologies to visualize and study the relationship between neurons, glial cells and blood vessels. In this paper, we present an overview of the current optical approaches used for the in vivo imaging of neurovascular coupling events in small animal models. These techniques include 2-photon microscopy, laser speckle contrast imaging (LSCI), voltage-sensitive dye imaging (VSDi), functional photoacoustic microscopy (fPAM), functional near-infrared spectroscopy imaging (fNIRS) and multimodal imaging techniques. The basic principles of each technique are described in detail, followed by examples of current applications from cutting-edge studies of cerebral neurovascular coupling functions and metabolic. Moreover, we provide a glimpse of the possible ways in which these techniques might be translated to human studies for clinical investigations of pathophysiology and disease. In vivo optical imaging techniques continue to expand and evolve, allowing us to discover fundamental basis of neurovascular coupling roles in cerebral physiology and pathophysiology.

Neural prostheses decode intention from cortical activity to restore upper extremity movement. Typical decoding algorithms extract velocity—a vector quantity with direction and magnitude (speed) —from neuronal firing rates. Standard decoding algorithms accurately recover arm direction, but the extraction of speed has proven more difficult. We show that this difficulty is due to the way speed is encoded by individual neurons and demonstrate how standard encoding-decoding procedures produce characteristic errors. These problems are addressed using alternative brain–computer interface (BCI) algorithms that accommodate nonlinear encoding of speed and direction. Our BCI approach leads to skillful control of both direction and speed as demonstrated by stereotypic bell-shaped speed profiles, straight trajectories, and steady cursor positions before and after the movement.

Developing models of the dynamic and complex patterns of information processing that take place during behavior is a major thrust of systems neuroscience. An underlying assumption of many models is that the same set of rules applies across different conditions. This has been the case for directional tuning during volitional movement; a single cosine function has been remarkably robust for describing the encoding of movement direction in different types of neurons, in many locations of the nervous system, and even across species. However, detailed examination of the tuning time course in motor cortex suggests that direction coding may be labile. Here, we show that there are discrete time epochs within single reaches, between which individual neurons change their tuning. Our findings suggest that motor cortical activity patterns may reflect consistent changes in the state of the control system during center-out reaching. These transitions are likely linked to different behavioral components, suggesting that the task defines changes in the operational structure of the control system.