Σφακιανάκης Αλέξανδρος
ΩτοΡινοΛαρυγγολόγος
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Τρίτη 21 Φεβρουαρίου 2017

Planar Implantable Sensor for In Vivo Measurement of Cellular Oxygen Metabolism in Brain Tissue

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Publication date: Available online 20 February 2017
Source:Journal of Neuroscience Methods
Author(s): Vassiliy Tsytsarev, Fatih Akkenti, Elena Pumbo, Qinggong Tang, Yu Chen, Reha S. Erzurumlu, Dmitri B. Papkovsky
BackgroundBrain imaging methods are continually improving. Imaging of the cerebral cortex is widely used in both animal experiments and charting human brain function in health and disease. Among the animal models, the rodent cerebral cortex has been widely used because of patterned neural representation of the whiskers on the snout and relative ease of activating cortical tissue with whisker stimulation.New MethodWe tested a new planar solid-state oxygen sensor comprising a polymeric film with a phosphorescent oxygen-sensitive coating on the working side, to monitor dynamics of oxygen metabolism in the cerebral cortex following sensory stimulation.ResultsSensory stimulation led to changes in oxygenation and deoxygenation processes of activated areas in the barrel cortex. We demonstrate the possibility of dynamic mapping of relative changes in oxygenation in live mouse brain tissue with such a sensor.Comparison with Existing MethodOxygenation-based functional magnetic resonance imaging (fMRI) is very effective method for functional brain mapping but have high costs and limited spatial resolution. Optical imaging of intrinsic signal (IOS) does not provide the required sensitivity, and voltage-sensitive dye optical imaging (VSDi) has limited applicability due to significant toxicity of the voltage-sensitive dye. Our planar solid-state oxygen sensor imaging approach circumvents these limitations, providing a simple optical contrast agent with low toxicity and rapid application.ConclusionsThe planar solid-state oxygen sensor described here can be used as a tool in visualization and real-time analysis of sensory-evoked neural activity in vivo. Further, this approach allows visualization of local neural activity with high temporal and spatial resolution.



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