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1.
medRxiv ; 2023 Nov 08.
Article in English | MEDLINE | ID: mdl-37986996

ABSTRACT

A reliable physiological biomarker for Major Depressive Disorder (MDD) is necessary to improve treatment success rates by shoring up variability in outcome measures. In this study, we establish a passive biomarker that tracks with changes in mood on the order of minutes to hours. We record from intracranial electrodes implanted deep in the brain - a surgical setting providing exquisite temporal and spatial sensitivity to detect this relationship in a difficult-to-measure brain area, the ventromedial prefrontal cortex (VMPFC). The aperiodic slope of the power spectral density captures the balance of activity across all frequency bands and is construed as a putative proxy for excitatory/inhibitory balance in the brain. This study demonstrates how shifts in aperiodic slope correlate with depression severity in a clinical trial of deep brain stimulation for treatment-resistant depression (TRD). The correlation between depression severity scores and aperiodic slope is significant in N=5 subjects, indicating that flatter (less negative) slopes correspond to reduced depression severity, especially in the ventromedial prefrontal cortex. This biomarker offers a new way to track patient response to MDD treatment, facilitating individualized therapies in both intracranial and non-invasive monitoring scenarios.

2.
J Neural Eng ; 18(1)2021 02 05.
Article in English | MEDLINE | ID: mdl-33152715

ABSTRACT

Objective.Researchers are developing biomedical devices with embedded closed-loop algorithms for providing advanced adaptive therapies. As these devices become more capable and algorithms become more complex, tasked with integrating and interpreting multi-channel, multi-modal electrophysiological signals, there is a need for flexible bench-top testing and prototyping. We present a methodology for leveraging off-the-shelf audio equipment to construct a biosignal waveform generator capable of streaming pre-recorded biosignals from a host computer. By re-playing known, well-characterized, but physiologically relevant real-world biosignals into a device under test, researchers can evaluate their systems without the need for expensivein vivoexperiments.Approach.An open-source design based on the proposed methodology is described and validated, the NeuroDAC. NeuroDAC allows for 8 independent channels of biosignal playback using a simple, custom designed attenuation and buffering circuit. Applications can communicate with the device over a USB interface using standard audio drivers. On-board analog amplitude adjustment is used to maximize the dynamic range for a given signal and can be independently tuned for each channel.Main results.Low noise component selection yields a no-signal noise floor of just 5.35 ± 0.063. NeuroDAC's frequency response is characterized with a high pass -3 dB rolloff at 0.57 Hz, and is capable of accurately reproducing a wide assortment of biosignals ranging from EMG, EEG, and ECG to extracellularly recorded neural activity. We also present an application example using the device to test embedded algorithms on a closed-loop neural modulation device, the Medtronic RC+S.Significance.By making the design of NeuroDAC open-source we aim to present an accessible tool for rapidly prototyping new biomedical devices and algorithms than can be easily modified based on individual testing needs.ClinicalTrials.gov Identifiers: NCT04281134, NCT03437928, NCT03582891.


Subject(s)
Algorithms , Electrophysiological Phenomena , Computers , Equipment Design , Signal Processing, Computer-Assisted
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