NON-INVASIVE ELECTROPHYSIOLOGICAL RECORDING OF DEEP NEURONS USING ULTRASOUND-INDUCED FREQUENCY SHIFTING AND DECODING

Acousto-electrophysiological neuroimaging (AENI) is an emerging technique for non-invasive recording of deep neuronal activity with millimeter spatial resolution based on ultrasound-induced frequency shifting of electrophysiological signals. When a focused ultrasound wave is applied to a target neuron, microscopic vibrations change the neuron–electrode distance, producing mixing between the neural signal and the ultrasound carrier at the recording electrode. This interaction shifts the spectral content of the targeted neuron’s activity into sidebands centered around the ultrasound frequency, while activity from non-target neurons remains confined to the baseband.Here, we investigate selective decoding of a single neuron embedded in a heterogeneous neural population. Using NetPyNE, we modeled a target neuron surrounded by 30 randomly positioned neurons. Ultrasound-induced vibration was applied exclusively to the target neuron, yielding composite local field potentials containing both frequency-shifted target activity and unshifted non-target activity.
Targeted activity was recovered using a frequency-domain decoding approach based on coherent demodulation to reconstruct the baseband waveform. This processing selectively extracts the shifted components while suppressing background interference. Simulation results demonstrate reliable recovery of the targeted neuron’s activity and a signal-to-interference ratio increase of up to 25 dB compared to the non-decoded case. Subsequently, we use the implemented AENI framework to study the decoded signal quality across cell types and ultrasonic protocols.
These results establish acousto-electric frequency shifting and decoding as an effective mechanism for spatially selective electrophysiological recording.