The in-vivo optical imaging of the cortical surface provides the ability to record different types of biophysiological signals, e.g., structural information, intrinsic signals, like blood oxygenation coupled reflection changes as well as extrinsic properties of voltage sensitive probes, like fluorescent voltage-sensitive dyes. The recorded data sets have very high temporal and spatial resolutions on a meso- to macroscopic scale, which surpass conventional multi-electrode recordings. Both, intrinsic and functional data sets, each provide unique information about temporal and spatial dynamics of cortical functioning, yet have individual drawbacks. To optimize the informational value it would thus be opportune to combine different types of optical imaging in a near simultaneous recording.Due to the low signal-to-noise ratio of voltage-sensitive dyes it is necessary to reduce stray light pollution below the level of the camera's dark noise. It is thus impossible to record full-spectrum optical data sets. We address this problem by a time-multiplexed illumination, bespoke to the utilized voltage sensitive dye, to record an alternating series of intrinsic and extrinsic frames by a high-frequency CMOS sensor. These near simultaneous data series can be used to compare the mutual influence of intrinsic and extrinsic dynamics (with regards to extracorporeal functional imaging) as well as for motion compensation and thus for minimizing frame averaging, which in turn results in increased spatial precision of functional data and in a reduction of necessary experimental data sets (3R principle).

Intracranial, functional optical imaging (OI) of intrinsic signals (like blood oxygenation coupled reflection changes) and of extrinsic properties of voltage sensitive probes (like voltage-sensitive dyes) belongs to a group of invasive neuroimaging techniques with very high temporal and spatial resolutions on a meso-to macroscopic scale. Voltage sensitive dye imaging (VSDI) images brain activity with low temporal delays, but the raw signal has a poor signal to noise ratio. An important pre-processing step for many biomedical imaging techniques is image registration and motion compensation. We can apply motion compensation successfully for optical imaging of intrinsic signals but VSDI recordings have low spatial contrast and often do not contain fine grained texture details which are crucial for successful image based motion compensation. In this work, we design a semi-synthetic dataset based on real recordings and a dummy voltage sensitive dye response for the evaluation of advanced motion compensation strategies for VSDI. This dataset aims to be used as a benchmark for the development of novel motion compensation strategies for VSDI and to derive error bounds of the methodologies with respect to motion.