Neuroscientists face a major challenge: separating real neural activity from background noise in extracellular recordings. This new study introduces adaptive virtual referencing, a breakthrough method that enhances neuron signal detection and improves data quality.
In the study titled “Adaptive Virtual Referencing for the Extraction of Extracellularly Recorded Action Potentials,” by Tim Allison-Walker et al, researchers developed an exciting novel method to enhance the detection of neuronal action potentials from extracellular recordings.
They employed 64 channel NeuroNexus silicon probes (A4x16-5mm-50-200-177) to capture high-fidelity neural signals. These silicon-based probes offer precise spatial resolution and are engineered to withstand the MRI’s magnetic environment, making them ideal for recording neuronal signals in challenging conditions. The adaptive virtual referencing technique improved the signal-to-noise ratio, enabling more accurate identification of neuronal activity. This advancement holds significant potential for improving the quality of data in neurophysiological research.
