Scientific Reports · 2018 · 58 citations · 55 references
EngineeringBiomedical EngineeringNeuroscienceBiomedical Signal ProcessingNeural EngineeringNeurophysiologyBiomedical InstrumentationMedical InstrumentationNeural InterfacesNeural Signal AcquisitionNeural Signal ProcessingNeurointerventional ProceduresClassification Accuracy AnalysisClassification Accuracy AssessmentImplantable Neural InterfacesMinimally Invasive ImplantationNeural RecordingNeural Signal RecordingSignal Quality AssessmentSignal-to-noise Ratio
Recent work has demonstrated the feasibility of minimally-invasive implantation of electrodes into a cortical blood vessel. However, the effect of the dura and blood vessel on recording signal quality is not understood and may be a critical factor impacting implementation of a closed-loop endovascular neuromodulation system. The present work compares the performance and recording signal quality of a minimally-invasive endovascular neural interface with conventional subdural and epidural interfaces. We compared bandwidth, signal-to-noise ratio, and spatial resolution of recorded cortical signals using subdural, epidural and endovascular arrays four weeks after implantation in sheep. We show that the quality of the signals (bandwidth and signal-to-noise ratio) of the endovascular neural interface is not significantly different from conventional neural sensors. However, the spatial resolution depends on the array location and the frequency of recording. We also show that there is a direct correlation between the signal-noise-ratio and classification accuracy, and that decoding accuracy is comparable between electrode arrays. These results support the consideration for use of an endovascular neural interface in a clinical trial of a novel closed-loop neuromodulation technology.
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Frequency Dependence of Signal Power and Spatial Reach of the Local Field Potential
NeuroGrid: recording action potentials from the surface of the brain
Dion Khodagholy, Jennifer N. Gelinas, Thomas Thesen et al. · Nature Neuroscience · 2014 · 954 citations · Full text
How Local Is the Local Field Potential?
Yoshinao Kajikawa, Charles E. Schroeder · Neuron · 2011 · 620 citations · Full text