YeonJoon Cheong

Acoustoelectric imaging (AEI) maps physiological current sources in tissue with spatiotemporal resolution set by the ultrasound pulse and beam. Conventional focused-beam scanning limits full 3D reconstruction due to the tradeoff between volume rate and field of view (FOV). Here, we present Hadamard synthetic beamforming (HSB) for full 3D AEI, along with strategies to reduce the transmit sequence for high-volume-rate imaging. This reduced-sequence HSB approach groups elements along one array dimension while applying transmit-focusing delays to preserve image quality and point spread function. Although this reduces subaperture elements and FOV in the encoded dimension, we quantify this limitation and show it is acceptable for biocurrent imaging. We validate the method using a 16 × 16 array at 0.6 MHz to image 200 Hz dipole sources in a tissue-mimicking phantom and through a 6 mm human skull at f/# = ~1. Reducing the sequence to 16 × 4 increases volume rate fourfold while maintaining a moderate-to-good elevation FOV of ±5.8°. At 10 cm depth with a 15 kHz pulse repetition frequency and 256 transmissions, volume rate increases from 58.6 to 234 Hz, sufficient to resolve gamma-band (~100 Hz) neural activity. Full HSB provides a theoretical SNR gain of 8.3 dB over focused-beam scanning after pressure equalization, while reduced-sequence HSB retains a 2.3 dB gain. Skull experiments confirm reduced-sequence HSB reconstructs 3D current fields comparable to full HSB. Most importantly, reduced-sequence HSB recovers all three current-density components at physiologically relevant volume rates over a practical imaging volume, impractical with conventional focused-beam scanning.

The human brain consists of multiple interacting neuronal networks that interleave at fine spatial and temporal scales. This complexity presents a challenge for scalp EEG and other noninvasive mapping techniques to accurately identify seizures and abnormal current patterns from background activity. To address this unmet need, this study investigates Transcranial Acoustoelectric Brain Imaging (tABI) with neuronavigation as a new method for mapping EEG-derived currents through the skull. In tABI, ultrasound (US) is focused and steered in the brain as surface electrodes record an acoustoelectric (AE) interaction signal. Space and time varying current maps are then generated at a resolution determined by the US focus. To test the efficacy of this method, a human skull was filled with conductive agarose gel, and a clinical depth electrode array was implanted 43 mm below the skull surface to generate artificial current waveform segments taken from normal and seizure activity. A 0.6 MHz 2D array was used to electronically focus and steer US through the skull while gold cup electrodes recorded high frequency AE signals and low frequency surface potentials. A 2D Wiener filter (WF) was introduced during preprocessing to enhance SNR followed by Singular Value Decomposition (SVD) to selectively identify pixels correlated with different temporal patterns. Whereas the WF enhanced SNR up to 16.9 dB at 6.4 mA of current, SVD enabled color-coding of tABI to highlight activation patterns correlated with different current waveforms with a spatial resolution of 5 mm. Finally, the current detection limit depended on the duration and bandwidth of the selected currents with the ictal waveform yielding the lowest detection (28 µA and 78 µA/cm2*MPa, p<0.05). These results support the development of tABI for noninvasive mapping of neuronal currents in epilepsy patients for surgical planning and other applications.

Acoustoelectric (AE) imaging has the potential to reconstruct current sources with high spatial and temporal resolution. However, a significant challenge is low signal-to-noise ratio (SNR), which complicates source detection and ultimately degrades spatial resolution. In this study, we propose a novel multi-electrode reconstruction method to image the current source density (CSD) in biological tissue at high image frame rates. This approach reconstructs the scalar potential of the current source with only single-step inversion regardless of the number of electrodes. It effectively removes modulation effects caused by acoustic and electrical-lead fields to obtain an unmodulated representation of the CSD. The approach was validated using a simple bio-mimicking cube phantom, with two stimulus electrodes to simulate current sources and six recording electrodes to capture AE signals. A 1.5D ultrasound transducer array operating at 0.6 MHz with focused beam scanning generated 2D AE signals for CSD reconstruction. Accurately modeled acoustic and lead fields were used in reconstruction through regularized inversion with truncated singular value decomposition (TSVD). The reconstructed scalar potential of the current source demonstrated improved spatial resolution with up to a 33 percent decrease in the area of the image point spread function and a 7 dB increase in SNR compared to raw AE signals for the small set of electrodes used. Moreover, the results were in strong agreement with simulated ground truth.

Acoustoelectric (AE) imaging has the potential to reconstruct current sources with high spatial and temporal resolution. However, a significant challenge is low signal-to-noise ratio (SNR), which complicates source detection and ultimately degrades spatial resolution. In this study, we propose a novel multi-electrode reconstruction method to image the current source density (CSD) in biological tissue at high image frame rates. This approach reconstructs the scalar potential of the current source with only single-step inversion regardless of the number of electrodes. It effectively removes modulation effects caused by acoustic and electrical-lead fields to obtain an unmodulated representation of the CSD. The approach was validated using a simple bio-mimicking cube phantom, with two stimulus electrodes to simulate current sources and six recording electrodes to capture AE signals. A 1.5D ultrasound transducer array operating at 0.6 MHz with focused beam scanning generated 2D AE signals for CSD reconstruction. Accurately modeled acoustic and lead fields were used in reconstruction through regularized inversion with truncated singular value decomposition (TSVD). The reconstructed scalar potential of the current source demonstrated improved spatial resolution with up to 33 percent decrease in the area of the image point spread function and a 7 dB increase in SNR compared to raw AE signals for the small set of electrodes used. Moreover, the results were in strong agreement with simulated ground truth.

Toothed whales possess specialized anatomical structures in the head, including thin, excavated lower mandible embedded in mandibular fat bodies, complex skull morphology fused with the upper jaw, and extensive air spaces surrounding the middle ears and beneath the skull. In this study, we use finite element modeling to investigate how these structures influence the transmission of water-borne sounds to the ears. The models are based on volumetric representations derived from computed tomography (CT) scans of a live bottlenose dolphin ( Tursiops truncatus ). We iteratively modify the anatomical structures included in the model and use the predicted head-related transfer functions (HRTFs) as a proxy for comparison. Our results show that the mandibular fat bodies, which support a lower sound speed than the surrounding tissues, significantly enhance the forward receiving directionality at echolocation frequencies through refraction, in a manner similar to the melon in shaping the dolphins’ highly directional transmission beams. Additionally, we show that, in the frequencies encompassing dolphin communication signals, the air volumes help block the otherwise complex sound transmission through the bones. These findings highlight convergent evolutionary solutions in toothed whale anatomy to create strong directionality in both sound emission and reception governed by the same physical principles.

This work introduces a paradigm for acoustic imaging in which a metasurface converts the acoustic waves scattered by remote scenes into coherent light focused into images by conventional optical cameras. The metasurface is composed of acousto-optical unit cells that sense the local acoustic pressure and use the resulting signal to modulate the amplitude of the electric field produced by a laser on an optical aperture. We derive the general design requirements for the image reconstruction in the optical domain and validate the concept through acoustic field measurements of the ultrasound scattered from an object submerged in water followed by numerical simulations predicting how this field is processed by the metasurface and camera. We show that this approach has two main advantages compared to traditional acoustic imaging systems. First, the acoustic-to-optic wavelength down-conversion leads to effective acoustical apertures very large compared to the physical size. Second, the unit cells are not synchronized electronically and thus the complexity of the metasurface increases only linearly with the number of unit cells, which is a significantly slower increase compared to conventional synchronized arrays. This work shows that these advantages lead to compact acoustic cameras providing image resolutions higher than possible with conventional acoustic imaging methods.