Simultaneous measurements of glucose, oxyhemoglobin and deoxyhemoglobin in exposed rat cortex

The present work addresses the simultaneous monitoring of hemoglobin and glucose consumption in rat somatosensory cortex in vivo. We propose a method which combines two techniques: 2-dimensional optical imaging and an amperometric microbiosensor. The mounted setup optimizes the space in the cranial window so that three micro-electrodes can be inserted: glucose microbiosensor, sentinel and stimulating electrode as well as the holder to manipulate the optical fiber. Additionally, a tool based on graphical user interface programming has been developed to visualize a two-dimension spectral map of oxy-, deoxy- and total hemoglobin, HbO2, HbR and HbT respectively, in the cortex. Our results showed a good sensitivity, selectivity and spatial resolution for both methods. Relevant hemodynamic responses had a common central focus (at the site of the stimulus) which later segregated to other vascular compartments. A good linear relationship between extracellular glucose concentration and HbO2 values during brain activation after local electrical stimulation was observed for electrochemical and optical recordings (R2 values were over 0.94). Time courses between glucose and HbO2 signals showed a temporal delay ranging from 1 s to 2 s, suggesting that both variables are not always coupled. The temporal mismatching reported here, provides in vivo evidence that supports a neuronal hypothesis: cerebral blow flow and oxidative metabolism are driven in parallel by neural activity – rather than a concatenation of events (‘in-series’ events) occurring at sites of neuronal activation.

► In this study we proposed an in vivo method to be used in exposed rat cortex. ► Two techniques have been combined: optical imaging and amperometric biosensor. ► We measure simultaneously hemoglobin and glucose signals after electrical stimulus. ► Temporal delay ranging from 1 ∼2 s between glucose and HbO2 signals was found. ► This result provides in vivo evidence that both variables are not always coupled.